int j remote sensing 2001 vol 22 no 10 1999ndash2014
A remote sensingndashGIS evaluation of urban expansion and its impacton surface temperature in the Zhujiang Delta China
Q WENGDepartment of Geography University of Alabama Tuscaloosa AL 35487 USA
(Received 26 May 1999 in nal form 22 November 1999)
Abstract The Zhujiang Delta of South China has experienced a rapid urbanexpansion over the past two decades due to accelerated economic growth Thispaper reports an investigation into the application of the integration of remotesensing and geographic information systems (GIS) for detecting urban growthand assessing its impact on surface temperature in the region Remote sensingtechniques were used to carry out land usecover change detection by usingmultitemporal Landsat Thematic Mapper data Urban growth patterns wereanalysed by using a GIS-based modelling approach The integration of remotesensing and GIS was further applied to examine the impact of urban growth onsurface temperatures The results revealed a notable and uneven urban growth inthe study area This urban development had raised surface radiant temperatureby 1301 K in the urbanized area The integration of remote sensing and GIS wasfound to be eVective in monitoring and analysing urban growth patterns and inevaluating urbanization impact on surface temperature
1 IntroductionLand covers as the biophysical state of the earthrsquos surface and immediate subsur-
face are sources and sinks for most of the material and energy movements andinteractions between the geosphere and biosphere Changes in land cover includechanges in biotic diversity actual and potential primary productivity soil qualityrunoV and sedimentation rates (SteVen et al 1992) and cannot be well understoodwithout the knowledge of land use change that drives them Therefore land use andland cover changes have environmental implications at local and regional levels andperhaps are linked to the global environmental process Because of the interrelatednature of the elements of the natural environment the direct eVects on one elementmay cause indirect eVects on others
Urbanization the conversion of other types of land to uses associated withgrowth of populations and economy is a main type of land use and land coverchange in human history It has a great impact on climate By covering with buildingsroads and other impervious surfaces urban areas generally have a higher solarradiation absorption and a greater thermal capacity and conductivity so that heatis stored during the day and released by night Therefore urban areas tend toexperience a relatively higher temperature compared with the surrounding ruralareas This thermal diVerence in conjunction with waste heat released from urbanhouses transportation and industry contribute to the development of urban heat
International Journal of Remote SensingISSN 0143-1161 printISSN 1366-5901 online copy 2001 Taylor amp Francis Ltd
httpwwwtandfcoukjournals
Q Weng2000
island (UHI) The temperature diVerence between the urban and the rural areas areusually modest averaging less than 1deg C but occasionally rising to several degreeswhen urban topographical and meteorological conditions are favourable for theUHI to develop (Mather 1986)
In China land use and land cover patterns have undergone a fundamental changedue to accelerated economic development under its economic reform policies since1978 Urban growth has been speeded up and extreme stress to the environmenthas occurred This is particularly true in the coastal region such as the ZhujiangDelta where massive agricultural land is disappearing each year converting to urbanor related uses Evaluating the magnitude and pattern of Chinarsquos urban growth isan urgent need Furthermore because of the lack of appropriate land use planningand the measures for sustainable development rampant urban growth has beencreating severe environmental consequences Thus there also is a need to assess theenvironmental impact of the rapid urban expansion
The integration of remote sensing and geographic information systems (GIS) hasbeen widely applied and been recognized as a powerful and eVective tool in detectingurban land use and land cover change (Ehlers et al 1990 Treitz et al 1992 Harrisand Ventura 1995) Satellite remote sensing collects multispectral multiresolutionand multitemporal data and turns them into information valuable for understand-ing and monitoring urban land processes and for building urban land cover datasetsGIS technology provides a exible environment for entering analysing and displayingdigital data from various sources necessary for urban feature identi cation changedetection and database development However few of the urban growth studies haslinked to post-change detection environmental impact analysis The question of howto develop an operational procedure using the existing techniques of remote sensingand GIS for examining environmental impacts of rapid urban growth remains to beanswered
The goal of this paper is to demonstrate the integrated use of remote sensingand GIS in addressing environmental issues in China at a local level Speci cobjectives are to evaluate urban growth patterns in the Zhujiang Delta and toanalyse the impact of the urban growth on surface temperature
2 Study areaThe study area the Zhujiang (literally lsquothe Pearl Riverrsquo) Delta is located between
latitudes 21deg 40 ecirc N and 23deg N and longitudes 112deg E and 113deg 20 ecirc E ( gures 1 and 2)It is the third biggest river delta in China and has an area of 17 200 km2 Because ofthe constraint of satellite data coverage this research focuses on the core area of thedelta that includes the following 15 citiescounties Guangzhou Panyu SanshuiNanhai Foshan Shunde Jiangmen Zhongshan Zhuhai Xinhui DoumenZengcheng Dongguan Baoan and Shenzhen Geomorphologically the ZhujiangDelta consists of three sub-deltas formed by sediments the Xijiang Beijiang andDonjiang Deltas originated approximately 40 thousand years ago (Department ofGeography Zhongshan University 1988) The process of sedimentation still con-tinues today extending seaward at a rate of 40 m per year (Gong and Chen 1964)The delta has a subtropical climate with an average annual temperature between 21and 23deg C and an average precipitation ranging from 1600 to 2600 mm Because ofthe impact of the East Asian Moonsoonal circulation about 80 of the rainfallcomes in the period of April to September with a concentration in the months ofMay to July when ooding is prone to occur (Ditu Chubanshe 1977) Another
A remote sensingndashGIS evaluation of urban expansion 2001
Figure 1 A map of the study area
hazard is typhoons which occur most frequently from June to October The deltarsquosfertile alluvial deposits in combination with the subtropical climate make it one ofthe richest agricultural areas in China The famous dikendashpond ecological agriculturalsystems and silk production can be traced back to the beginning of the Ming Dynasty(1368ndash1644 AD) (Zhong 1980 Ruddle and Zhong 1988)
Economically the Zhujiang Delta is the largest area of economic concentrationin South China Guangzhou Chinarsquos sixth largest city Hong Kong and Macao arelocated here Since 1978 the delta has become a rising star due to its dramaticeconomic expansion under Chinarsquos economic reform policies and therefore has beenregarded as a model for Chinese regional development The establishment ofShenzhen and Zhuhai Special Economic Zones in 1979 and the Zhujiang DeltaEconomic Open Zone in 1985 has stimulated Hong Kong and foreign rms to locatetheir factories there as villagendashtownship enterprises The labour-intensive industriesin association with the cash crop production notably seafood poultry vegetablesfruit and owers have transformed the spatial economy of the delta (Lo 1989 Weng1998) The rapid economic development has brought about fundamental changes inland use and land cover patterns The integrated approach developed in this paperis to analyse the changing patterns of urban land usecover and its impact on surfacetemperature
Q Weng2002
Figure 2 Major rivers counties and cities in the Zhujiang Delta (after Lo 1989)
3 Methodology31 Urban expansion detection and analysis
Land usecover patterns for 1989 and 1997 were mapped by the use of LandsatThematic Mapper (TM) data (Dates 13 December 1989 and 29 August 1997) Sevenland use and land cover types are identi ed and used in this study including(1) urban or built-up land (2) barren land (3) cropland (4) horticulture farms(5) dikendashpond land (6) forest and (7) water With the aid of Erdas Imagine computersoftware each Landsat image was enhanced using histogram equalization (in orderto gain a higher contrast in the lsquopeaksrsquo of the original histogram) to increase thevolume of visible information This procedure is important for helping identifyground control points in recti cation All images are recti ed to a common UTM(Universal Transverse Mercator) coordinate system based on the 1550 000 topo-graphic maps of Guangdong Province produced by the Chinese government Eachimage was then radiometrically corrected using relative radiometric correctionmethod (Jensen 1996) A supervised classi cation with the maximum likelihoodalgorithm was conducted to classify the Landsat images using bands 2 (green) 3 (red)and 4 (near-infrared) The accuracy of the classi cation was veri ed by eld checkingor comparing with existing land use and cover maps that have been eld-checked
In performing land usecover change detection a cross-tabulation detectionmethod was employed A change matrix was produced with the help of ErdasImagine software Quantitative areal data of the overall land usecover changes aswell as gains and losses in each category between 1989 and 1997 were then compiledIn order to analyse the nature rate and location of urban land change an image ofurban and built-up land was extracted from each original land cover image The
A remote sensingndashGIS evaluation of urban expansion 2003
extracted images were then overlaid and recoded to obtain an urban land change(expansion) image
The urban expansion image was further overlaid with several geographic referenceimages to help analyse the patterns of urban expansion including an image of thecountycity boundary major roads and major urban centres These layers wereconstructed in a vector GIS environment and converted into a raster format (gridsize=30 m) The countycity boundary image can be utilized to nd urban landchange information within each countycity Because proximity to a certain objectsuch as major roads has an important implication in urban land development urbanexpansion processes often show an intimate relationship with distance from thesegeographic objects Using the buVer function in GIS a buVer image was generatedshowing the proximity to the major roads of the study area Ten buVer zones werecreated around a major road with a width of 500 m Local conditions have beentaken into account in selecting these buVer widths The buVer image was overlaidwith the urban expansion image to calculate the amount of urban expansion in eachzone The density of urban expansion was then calculated by dividing the amountof urban expansion by the total amount of land in each buVer zone These valuesof density can be used to construct a distance decay function of urban expansion
32 Urbanization expansion impact analysisUrban development usually gives rise to a dramatic change of the Earthrsquos surface
as natural vegetation is removed and replaced by non-evaporating and non-transpiring surfaces such as metal asphalt and concrete This alteration will inevitablyresult in the redistribution of incoming solar radiation and induce the urbanndashruralcontrast in surface radiance and air temperature The diVerence in ambient airtemperature between an urban and its surrounding rural area is known as the eVectof UHI Given the relationship between surface radiant temperature and the textureof land cover the impact of urban development on surface temperature in theZhujiang Delta can be assessed
Studies on surface temperature characteristics of urban areas using satelliteremote sensing data have been conducted primarily using NOAA AVHRR data(Kidder and Wu 1987 Balling and Brazell 1988 Roth et al 1989 Gallo et al 1993a)The 11 km spatial resolution of these data are found suitable only for small-scaleurban temperature mapping The much higher resolution (120 m) Landsat TMthermal infrared data were seldom used to derive surface temperature RecentlyCarnahan and Larson (1990) have used the TM thermal infrared data to observemesoscale temperature diVerences between urban and rural areas in Indianapoliswhile Nichol (1994) used it to monitor microclimate for some housing estates inSingapore However no research has yet attempted to detect urban-induced surfacetemperature change over time at a local level using multidate TM thermal infrareddata
To measure the surface temperature change from 1989 to 1997 surface radianttemperatures were derived from radiometrically corrected TM thermal infrared data(band 6) using the following quadratic model to convert the digital number (DN)into radiant temperatures (Malaret et al 1985 )
T (K)=209831+0834 DN shy 000133 DN2 (1)
Then corrections for emissivity (e) were applied to the radiant temperatures accordingto the nature of land cover In general vegetated areas were given a value of 095
Q Weng2004
and non-vegetated areas 092 (Nichol 1994) The emissivity corrected surface temper-ature can be computed as follows (Artis and Carnahan 1982)
Ts=
T (K )
1+(lT (K)a) ln e(2)
where l=wavelength of emitted radiance (for which the peak response and theaverage of the limiting wavelengths (l=115 mm) (Markham and Barker 1985)will be used) a=hcK (1438times10 Otilde 2 mK) K=Stefan Boltzmannrsquos constant(138times10Otilde 23 J K Otilde 1) h=Planckrsquos constant (626times10Otilde 34 J s) and c=velocity of light(2998times108 s Otilde 1)
In examining the spatial relationship between land usecover types and the surfaceenergy response as measured by Ts the classi ed land cover images in 1989 and1997 were overlaid to the Ts image of corresponding years Because normalizeddiVerence vegetation index (NDVI) has been found to be a good indicator of surfaceradiant temperature (Nemani and Running 1989 Gallo et al 1993b Gillies andCarlson 1995 Lo et al 1997) a NDVI image was computed for 1989 and 1997 fromvisible (063ndash069 mm) and near-infrared (076ndash090 mm) data of the Landsat TMusing the following formula
NDVI=TM4 shy TM3TM4+TM3
(3)
The resultant NDVI image was overlaid with the Ts
image for each year In thisway the interactions among land usecover NDVI and surface temperature can berevealed
Surface temperature change image between 1989 and 1997 was also producedusing image diVerencing This image was overlaid with the land usecover changemap and with the NDVI change map to study how all these changes have interacted
4 Results and discussion41 Urban expansion in the Zhujiang Delta 1989ndash1997
The overall accuracy of the land usecover map for 1989 and 1997 were deter-mined to be 9057 and 8543 respectively (tables 1 and 2) The Kappa indicesfor the 1989 and 1997 maps were 08905 and 08317 respectively Clearly these datahave reasonably high accuracy and thus are suYcient for urban growth detection
Table 3 shows the land use and land cover change matrix of the Zhujiang Deltafrom 1989 to 1997 From this table it is clear that there has been a considerablechange (1282 of the total area) in land use and land cover in the study area duringthe 8-year period Urban or built-up land and horticulture farms have increased inarea (by 4768 and 8866 respectively) and cropland has decreased in area (by4837 )
The overlay of the 1989 and 1997 land usecover map further indicates that ofthe 4768 (65 690 ha) increase in urban or built-up land most results from cropland(3792 ) and horticulture farms (1605 ) Figure 3 shows the areal extent andspatial occurrence of the urban expansion The overlay of this map with a cityndashcounty mask reveals the spatial occurrence of urban expansion within administrativeregions Table 4 shows that in absolute term the greatest urban expansion occurredin Dongguan (23 47890 ha) Baoan (14 94108 ha) Nanhai (80041 ha) and Zhuhai(586971 ha) However in percentage terms the largest increase in urban or built-upland occurred in Zhuhai (110000 ) followed by Shenzhen (30665 ) Baoan
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2000
island (UHI) The temperature diVerence between the urban and the rural areas areusually modest averaging less than 1deg C but occasionally rising to several degreeswhen urban topographical and meteorological conditions are favourable for theUHI to develop (Mather 1986)
In China land use and land cover patterns have undergone a fundamental changedue to accelerated economic development under its economic reform policies since1978 Urban growth has been speeded up and extreme stress to the environmenthas occurred This is particularly true in the coastal region such as the ZhujiangDelta where massive agricultural land is disappearing each year converting to urbanor related uses Evaluating the magnitude and pattern of Chinarsquos urban growth isan urgent need Furthermore because of the lack of appropriate land use planningand the measures for sustainable development rampant urban growth has beencreating severe environmental consequences Thus there also is a need to assess theenvironmental impact of the rapid urban expansion
The integration of remote sensing and geographic information systems (GIS) hasbeen widely applied and been recognized as a powerful and eVective tool in detectingurban land use and land cover change (Ehlers et al 1990 Treitz et al 1992 Harrisand Ventura 1995) Satellite remote sensing collects multispectral multiresolutionand multitemporal data and turns them into information valuable for understand-ing and monitoring urban land processes and for building urban land cover datasetsGIS technology provides a exible environment for entering analysing and displayingdigital data from various sources necessary for urban feature identi cation changedetection and database development However few of the urban growth studies haslinked to post-change detection environmental impact analysis The question of howto develop an operational procedure using the existing techniques of remote sensingand GIS for examining environmental impacts of rapid urban growth remains to beanswered
The goal of this paper is to demonstrate the integrated use of remote sensingand GIS in addressing environmental issues in China at a local level Speci cobjectives are to evaluate urban growth patterns in the Zhujiang Delta and toanalyse the impact of the urban growth on surface temperature
2 Study areaThe study area the Zhujiang (literally lsquothe Pearl Riverrsquo) Delta is located between
latitudes 21deg 40 ecirc N and 23deg N and longitudes 112deg E and 113deg 20 ecirc E ( gures 1 and 2)It is the third biggest river delta in China and has an area of 17 200 km2 Because ofthe constraint of satellite data coverage this research focuses on the core area of thedelta that includes the following 15 citiescounties Guangzhou Panyu SanshuiNanhai Foshan Shunde Jiangmen Zhongshan Zhuhai Xinhui DoumenZengcheng Dongguan Baoan and Shenzhen Geomorphologically the ZhujiangDelta consists of three sub-deltas formed by sediments the Xijiang Beijiang andDonjiang Deltas originated approximately 40 thousand years ago (Department ofGeography Zhongshan University 1988) The process of sedimentation still con-tinues today extending seaward at a rate of 40 m per year (Gong and Chen 1964)The delta has a subtropical climate with an average annual temperature between 21and 23deg C and an average precipitation ranging from 1600 to 2600 mm Because ofthe impact of the East Asian Moonsoonal circulation about 80 of the rainfallcomes in the period of April to September with a concentration in the months ofMay to July when ooding is prone to occur (Ditu Chubanshe 1977) Another
A remote sensingndashGIS evaluation of urban expansion 2001
Figure 1 A map of the study area
hazard is typhoons which occur most frequently from June to October The deltarsquosfertile alluvial deposits in combination with the subtropical climate make it one ofthe richest agricultural areas in China The famous dikendashpond ecological agriculturalsystems and silk production can be traced back to the beginning of the Ming Dynasty(1368ndash1644 AD) (Zhong 1980 Ruddle and Zhong 1988)
Economically the Zhujiang Delta is the largest area of economic concentrationin South China Guangzhou Chinarsquos sixth largest city Hong Kong and Macao arelocated here Since 1978 the delta has become a rising star due to its dramaticeconomic expansion under Chinarsquos economic reform policies and therefore has beenregarded as a model for Chinese regional development The establishment ofShenzhen and Zhuhai Special Economic Zones in 1979 and the Zhujiang DeltaEconomic Open Zone in 1985 has stimulated Hong Kong and foreign rms to locatetheir factories there as villagendashtownship enterprises The labour-intensive industriesin association with the cash crop production notably seafood poultry vegetablesfruit and owers have transformed the spatial economy of the delta (Lo 1989 Weng1998) The rapid economic development has brought about fundamental changes inland use and land cover patterns The integrated approach developed in this paperis to analyse the changing patterns of urban land usecover and its impact on surfacetemperature
Q Weng2002
Figure 2 Major rivers counties and cities in the Zhujiang Delta (after Lo 1989)
3 Methodology31 Urban expansion detection and analysis
Land usecover patterns for 1989 and 1997 were mapped by the use of LandsatThematic Mapper (TM) data (Dates 13 December 1989 and 29 August 1997) Sevenland use and land cover types are identi ed and used in this study including(1) urban or built-up land (2) barren land (3) cropland (4) horticulture farms(5) dikendashpond land (6) forest and (7) water With the aid of Erdas Imagine computersoftware each Landsat image was enhanced using histogram equalization (in orderto gain a higher contrast in the lsquopeaksrsquo of the original histogram) to increase thevolume of visible information This procedure is important for helping identifyground control points in recti cation All images are recti ed to a common UTM(Universal Transverse Mercator) coordinate system based on the 1550 000 topo-graphic maps of Guangdong Province produced by the Chinese government Eachimage was then radiometrically corrected using relative radiometric correctionmethod (Jensen 1996) A supervised classi cation with the maximum likelihoodalgorithm was conducted to classify the Landsat images using bands 2 (green) 3 (red)and 4 (near-infrared) The accuracy of the classi cation was veri ed by eld checkingor comparing with existing land use and cover maps that have been eld-checked
In performing land usecover change detection a cross-tabulation detectionmethod was employed A change matrix was produced with the help of ErdasImagine software Quantitative areal data of the overall land usecover changes aswell as gains and losses in each category between 1989 and 1997 were then compiledIn order to analyse the nature rate and location of urban land change an image ofurban and built-up land was extracted from each original land cover image The
A remote sensingndashGIS evaluation of urban expansion 2003
extracted images were then overlaid and recoded to obtain an urban land change(expansion) image
The urban expansion image was further overlaid with several geographic referenceimages to help analyse the patterns of urban expansion including an image of thecountycity boundary major roads and major urban centres These layers wereconstructed in a vector GIS environment and converted into a raster format (gridsize=30 m) The countycity boundary image can be utilized to nd urban landchange information within each countycity Because proximity to a certain objectsuch as major roads has an important implication in urban land development urbanexpansion processes often show an intimate relationship with distance from thesegeographic objects Using the buVer function in GIS a buVer image was generatedshowing the proximity to the major roads of the study area Ten buVer zones werecreated around a major road with a width of 500 m Local conditions have beentaken into account in selecting these buVer widths The buVer image was overlaidwith the urban expansion image to calculate the amount of urban expansion in eachzone The density of urban expansion was then calculated by dividing the amountof urban expansion by the total amount of land in each buVer zone These valuesof density can be used to construct a distance decay function of urban expansion
32 Urbanization expansion impact analysisUrban development usually gives rise to a dramatic change of the Earthrsquos surface
as natural vegetation is removed and replaced by non-evaporating and non-transpiring surfaces such as metal asphalt and concrete This alteration will inevitablyresult in the redistribution of incoming solar radiation and induce the urbanndashruralcontrast in surface radiance and air temperature The diVerence in ambient airtemperature between an urban and its surrounding rural area is known as the eVectof UHI Given the relationship between surface radiant temperature and the textureof land cover the impact of urban development on surface temperature in theZhujiang Delta can be assessed
Studies on surface temperature characteristics of urban areas using satelliteremote sensing data have been conducted primarily using NOAA AVHRR data(Kidder and Wu 1987 Balling and Brazell 1988 Roth et al 1989 Gallo et al 1993a)The 11 km spatial resolution of these data are found suitable only for small-scaleurban temperature mapping The much higher resolution (120 m) Landsat TMthermal infrared data were seldom used to derive surface temperature RecentlyCarnahan and Larson (1990) have used the TM thermal infrared data to observemesoscale temperature diVerences between urban and rural areas in Indianapoliswhile Nichol (1994) used it to monitor microclimate for some housing estates inSingapore However no research has yet attempted to detect urban-induced surfacetemperature change over time at a local level using multidate TM thermal infrareddata
To measure the surface temperature change from 1989 to 1997 surface radianttemperatures were derived from radiometrically corrected TM thermal infrared data(band 6) using the following quadratic model to convert the digital number (DN)into radiant temperatures (Malaret et al 1985 )
T (K)=209831+0834 DN shy 000133 DN2 (1)
Then corrections for emissivity (e) were applied to the radiant temperatures accordingto the nature of land cover In general vegetated areas were given a value of 095
Q Weng2004
and non-vegetated areas 092 (Nichol 1994) The emissivity corrected surface temper-ature can be computed as follows (Artis and Carnahan 1982)
Ts=
T (K )
1+(lT (K)a) ln e(2)
where l=wavelength of emitted radiance (for which the peak response and theaverage of the limiting wavelengths (l=115 mm) (Markham and Barker 1985)will be used) a=hcK (1438times10 Otilde 2 mK) K=Stefan Boltzmannrsquos constant(138times10Otilde 23 J K Otilde 1) h=Planckrsquos constant (626times10Otilde 34 J s) and c=velocity of light(2998times108 s Otilde 1)
In examining the spatial relationship between land usecover types and the surfaceenergy response as measured by Ts the classi ed land cover images in 1989 and1997 were overlaid to the Ts image of corresponding years Because normalizeddiVerence vegetation index (NDVI) has been found to be a good indicator of surfaceradiant temperature (Nemani and Running 1989 Gallo et al 1993b Gillies andCarlson 1995 Lo et al 1997) a NDVI image was computed for 1989 and 1997 fromvisible (063ndash069 mm) and near-infrared (076ndash090 mm) data of the Landsat TMusing the following formula
NDVI=TM4 shy TM3TM4+TM3
(3)
The resultant NDVI image was overlaid with the Ts
image for each year In thisway the interactions among land usecover NDVI and surface temperature can berevealed
Surface temperature change image between 1989 and 1997 was also producedusing image diVerencing This image was overlaid with the land usecover changemap and with the NDVI change map to study how all these changes have interacted
4 Results and discussion41 Urban expansion in the Zhujiang Delta 1989ndash1997
The overall accuracy of the land usecover map for 1989 and 1997 were deter-mined to be 9057 and 8543 respectively (tables 1 and 2) The Kappa indicesfor the 1989 and 1997 maps were 08905 and 08317 respectively Clearly these datahave reasonably high accuracy and thus are suYcient for urban growth detection
Table 3 shows the land use and land cover change matrix of the Zhujiang Deltafrom 1989 to 1997 From this table it is clear that there has been a considerablechange (1282 of the total area) in land use and land cover in the study area duringthe 8-year period Urban or built-up land and horticulture farms have increased inarea (by 4768 and 8866 respectively) and cropland has decreased in area (by4837 )
The overlay of the 1989 and 1997 land usecover map further indicates that ofthe 4768 (65 690 ha) increase in urban or built-up land most results from cropland(3792 ) and horticulture farms (1605 ) Figure 3 shows the areal extent andspatial occurrence of the urban expansion The overlay of this map with a cityndashcounty mask reveals the spatial occurrence of urban expansion within administrativeregions Table 4 shows that in absolute term the greatest urban expansion occurredin Dongguan (23 47890 ha) Baoan (14 94108 ha) Nanhai (80041 ha) and Zhuhai(586971 ha) However in percentage terms the largest increase in urban or built-upland occurred in Zhuhai (110000 ) followed by Shenzhen (30665 ) Baoan
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2001
Figure 1 A map of the study area
hazard is typhoons which occur most frequently from June to October The deltarsquosfertile alluvial deposits in combination with the subtropical climate make it one ofthe richest agricultural areas in China The famous dikendashpond ecological agriculturalsystems and silk production can be traced back to the beginning of the Ming Dynasty(1368ndash1644 AD) (Zhong 1980 Ruddle and Zhong 1988)
Economically the Zhujiang Delta is the largest area of economic concentrationin South China Guangzhou Chinarsquos sixth largest city Hong Kong and Macao arelocated here Since 1978 the delta has become a rising star due to its dramaticeconomic expansion under Chinarsquos economic reform policies and therefore has beenregarded as a model for Chinese regional development The establishment ofShenzhen and Zhuhai Special Economic Zones in 1979 and the Zhujiang DeltaEconomic Open Zone in 1985 has stimulated Hong Kong and foreign rms to locatetheir factories there as villagendashtownship enterprises The labour-intensive industriesin association with the cash crop production notably seafood poultry vegetablesfruit and owers have transformed the spatial economy of the delta (Lo 1989 Weng1998) The rapid economic development has brought about fundamental changes inland use and land cover patterns The integrated approach developed in this paperis to analyse the changing patterns of urban land usecover and its impact on surfacetemperature
Q Weng2002
Figure 2 Major rivers counties and cities in the Zhujiang Delta (after Lo 1989)
3 Methodology31 Urban expansion detection and analysis
Land usecover patterns for 1989 and 1997 were mapped by the use of LandsatThematic Mapper (TM) data (Dates 13 December 1989 and 29 August 1997) Sevenland use and land cover types are identi ed and used in this study including(1) urban or built-up land (2) barren land (3) cropland (4) horticulture farms(5) dikendashpond land (6) forest and (7) water With the aid of Erdas Imagine computersoftware each Landsat image was enhanced using histogram equalization (in orderto gain a higher contrast in the lsquopeaksrsquo of the original histogram) to increase thevolume of visible information This procedure is important for helping identifyground control points in recti cation All images are recti ed to a common UTM(Universal Transverse Mercator) coordinate system based on the 1550 000 topo-graphic maps of Guangdong Province produced by the Chinese government Eachimage was then radiometrically corrected using relative radiometric correctionmethod (Jensen 1996) A supervised classi cation with the maximum likelihoodalgorithm was conducted to classify the Landsat images using bands 2 (green) 3 (red)and 4 (near-infrared) The accuracy of the classi cation was veri ed by eld checkingor comparing with existing land use and cover maps that have been eld-checked
In performing land usecover change detection a cross-tabulation detectionmethod was employed A change matrix was produced with the help of ErdasImagine software Quantitative areal data of the overall land usecover changes aswell as gains and losses in each category between 1989 and 1997 were then compiledIn order to analyse the nature rate and location of urban land change an image ofurban and built-up land was extracted from each original land cover image The
A remote sensingndashGIS evaluation of urban expansion 2003
extracted images were then overlaid and recoded to obtain an urban land change(expansion) image
The urban expansion image was further overlaid with several geographic referenceimages to help analyse the patterns of urban expansion including an image of thecountycity boundary major roads and major urban centres These layers wereconstructed in a vector GIS environment and converted into a raster format (gridsize=30 m) The countycity boundary image can be utilized to nd urban landchange information within each countycity Because proximity to a certain objectsuch as major roads has an important implication in urban land development urbanexpansion processes often show an intimate relationship with distance from thesegeographic objects Using the buVer function in GIS a buVer image was generatedshowing the proximity to the major roads of the study area Ten buVer zones werecreated around a major road with a width of 500 m Local conditions have beentaken into account in selecting these buVer widths The buVer image was overlaidwith the urban expansion image to calculate the amount of urban expansion in eachzone The density of urban expansion was then calculated by dividing the amountof urban expansion by the total amount of land in each buVer zone These valuesof density can be used to construct a distance decay function of urban expansion
32 Urbanization expansion impact analysisUrban development usually gives rise to a dramatic change of the Earthrsquos surface
as natural vegetation is removed and replaced by non-evaporating and non-transpiring surfaces such as metal asphalt and concrete This alteration will inevitablyresult in the redistribution of incoming solar radiation and induce the urbanndashruralcontrast in surface radiance and air temperature The diVerence in ambient airtemperature between an urban and its surrounding rural area is known as the eVectof UHI Given the relationship between surface radiant temperature and the textureof land cover the impact of urban development on surface temperature in theZhujiang Delta can be assessed
Studies on surface temperature characteristics of urban areas using satelliteremote sensing data have been conducted primarily using NOAA AVHRR data(Kidder and Wu 1987 Balling and Brazell 1988 Roth et al 1989 Gallo et al 1993a)The 11 km spatial resolution of these data are found suitable only for small-scaleurban temperature mapping The much higher resolution (120 m) Landsat TMthermal infrared data were seldom used to derive surface temperature RecentlyCarnahan and Larson (1990) have used the TM thermal infrared data to observemesoscale temperature diVerences between urban and rural areas in Indianapoliswhile Nichol (1994) used it to monitor microclimate for some housing estates inSingapore However no research has yet attempted to detect urban-induced surfacetemperature change over time at a local level using multidate TM thermal infrareddata
To measure the surface temperature change from 1989 to 1997 surface radianttemperatures were derived from radiometrically corrected TM thermal infrared data(band 6) using the following quadratic model to convert the digital number (DN)into radiant temperatures (Malaret et al 1985 )
T (K)=209831+0834 DN shy 000133 DN2 (1)
Then corrections for emissivity (e) were applied to the radiant temperatures accordingto the nature of land cover In general vegetated areas were given a value of 095
Q Weng2004
and non-vegetated areas 092 (Nichol 1994) The emissivity corrected surface temper-ature can be computed as follows (Artis and Carnahan 1982)
Ts=
T (K )
1+(lT (K)a) ln e(2)
where l=wavelength of emitted radiance (for which the peak response and theaverage of the limiting wavelengths (l=115 mm) (Markham and Barker 1985)will be used) a=hcK (1438times10 Otilde 2 mK) K=Stefan Boltzmannrsquos constant(138times10Otilde 23 J K Otilde 1) h=Planckrsquos constant (626times10Otilde 34 J s) and c=velocity of light(2998times108 s Otilde 1)
In examining the spatial relationship between land usecover types and the surfaceenergy response as measured by Ts the classi ed land cover images in 1989 and1997 were overlaid to the Ts image of corresponding years Because normalizeddiVerence vegetation index (NDVI) has been found to be a good indicator of surfaceradiant temperature (Nemani and Running 1989 Gallo et al 1993b Gillies andCarlson 1995 Lo et al 1997) a NDVI image was computed for 1989 and 1997 fromvisible (063ndash069 mm) and near-infrared (076ndash090 mm) data of the Landsat TMusing the following formula
NDVI=TM4 shy TM3TM4+TM3
(3)
The resultant NDVI image was overlaid with the Ts
image for each year In thisway the interactions among land usecover NDVI and surface temperature can berevealed
Surface temperature change image between 1989 and 1997 was also producedusing image diVerencing This image was overlaid with the land usecover changemap and with the NDVI change map to study how all these changes have interacted
4 Results and discussion41 Urban expansion in the Zhujiang Delta 1989ndash1997
The overall accuracy of the land usecover map for 1989 and 1997 were deter-mined to be 9057 and 8543 respectively (tables 1 and 2) The Kappa indicesfor the 1989 and 1997 maps were 08905 and 08317 respectively Clearly these datahave reasonably high accuracy and thus are suYcient for urban growth detection
Table 3 shows the land use and land cover change matrix of the Zhujiang Deltafrom 1989 to 1997 From this table it is clear that there has been a considerablechange (1282 of the total area) in land use and land cover in the study area duringthe 8-year period Urban or built-up land and horticulture farms have increased inarea (by 4768 and 8866 respectively) and cropland has decreased in area (by4837 )
The overlay of the 1989 and 1997 land usecover map further indicates that ofthe 4768 (65 690 ha) increase in urban or built-up land most results from cropland(3792 ) and horticulture farms (1605 ) Figure 3 shows the areal extent andspatial occurrence of the urban expansion The overlay of this map with a cityndashcounty mask reveals the spatial occurrence of urban expansion within administrativeregions Table 4 shows that in absolute term the greatest urban expansion occurredin Dongguan (23 47890 ha) Baoan (14 94108 ha) Nanhai (80041 ha) and Zhuhai(586971 ha) However in percentage terms the largest increase in urban or built-upland occurred in Zhuhai (110000 ) followed by Shenzhen (30665 ) Baoan
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2002
Figure 2 Major rivers counties and cities in the Zhujiang Delta (after Lo 1989)
3 Methodology31 Urban expansion detection and analysis
Land usecover patterns for 1989 and 1997 were mapped by the use of LandsatThematic Mapper (TM) data (Dates 13 December 1989 and 29 August 1997) Sevenland use and land cover types are identi ed and used in this study including(1) urban or built-up land (2) barren land (3) cropland (4) horticulture farms(5) dikendashpond land (6) forest and (7) water With the aid of Erdas Imagine computersoftware each Landsat image was enhanced using histogram equalization (in orderto gain a higher contrast in the lsquopeaksrsquo of the original histogram) to increase thevolume of visible information This procedure is important for helping identifyground control points in recti cation All images are recti ed to a common UTM(Universal Transverse Mercator) coordinate system based on the 1550 000 topo-graphic maps of Guangdong Province produced by the Chinese government Eachimage was then radiometrically corrected using relative radiometric correctionmethod (Jensen 1996) A supervised classi cation with the maximum likelihoodalgorithm was conducted to classify the Landsat images using bands 2 (green) 3 (red)and 4 (near-infrared) The accuracy of the classi cation was veri ed by eld checkingor comparing with existing land use and cover maps that have been eld-checked
In performing land usecover change detection a cross-tabulation detectionmethod was employed A change matrix was produced with the help of ErdasImagine software Quantitative areal data of the overall land usecover changes aswell as gains and losses in each category between 1989 and 1997 were then compiledIn order to analyse the nature rate and location of urban land change an image ofurban and built-up land was extracted from each original land cover image The
A remote sensingndashGIS evaluation of urban expansion 2003
extracted images were then overlaid and recoded to obtain an urban land change(expansion) image
The urban expansion image was further overlaid with several geographic referenceimages to help analyse the patterns of urban expansion including an image of thecountycity boundary major roads and major urban centres These layers wereconstructed in a vector GIS environment and converted into a raster format (gridsize=30 m) The countycity boundary image can be utilized to nd urban landchange information within each countycity Because proximity to a certain objectsuch as major roads has an important implication in urban land development urbanexpansion processes often show an intimate relationship with distance from thesegeographic objects Using the buVer function in GIS a buVer image was generatedshowing the proximity to the major roads of the study area Ten buVer zones werecreated around a major road with a width of 500 m Local conditions have beentaken into account in selecting these buVer widths The buVer image was overlaidwith the urban expansion image to calculate the amount of urban expansion in eachzone The density of urban expansion was then calculated by dividing the amountof urban expansion by the total amount of land in each buVer zone These valuesof density can be used to construct a distance decay function of urban expansion
32 Urbanization expansion impact analysisUrban development usually gives rise to a dramatic change of the Earthrsquos surface
as natural vegetation is removed and replaced by non-evaporating and non-transpiring surfaces such as metal asphalt and concrete This alteration will inevitablyresult in the redistribution of incoming solar radiation and induce the urbanndashruralcontrast in surface radiance and air temperature The diVerence in ambient airtemperature between an urban and its surrounding rural area is known as the eVectof UHI Given the relationship between surface radiant temperature and the textureof land cover the impact of urban development on surface temperature in theZhujiang Delta can be assessed
Studies on surface temperature characteristics of urban areas using satelliteremote sensing data have been conducted primarily using NOAA AVHRR data(Kidder and Wu 1987 Balling and Brazell 1988 Roth et al 1989 Gallo et al 1993a)The 11 km spatial resolution of these data are found suitable only for small-scaleurban temperature mapping The much higher resolution (120 m) Landsat TMthermal infrared data were seldom used to derive surface temperature RecentlyCarnahan and Larson (1990) have used the TM thermal infrared data to observemesoscale temperature diVerences between urban and rural areas in Indianapoliswhile Nichol (1994) used it to monitor microclimate for some housing estates inSingapore However no research has yet attempted to detect urban-induced surfacetemperature change over time at a local level using multidate TM thermal infrareddata
To measure the surface temperature change from 1989 to 1997 surface radianttemperatures were derived from radiometrically corrected TM thermal infrared data(band 6) using the following quadratic model to convert the digital number (DN)into radiant temperatures (Malaret et al 1985 )
T (K)=209831+0834 DN shy 000133 DN2 (1)
Then corrections for emissivity (e) were applied to the radiant temperatures accordingto the nature of land cover In general vegetated areas were given a value of 095
Q Weng2004
and non-vegetated areas 092 (Nichol 1994) The emissivity corrected surface temper-ature can be computed as follows (Artis and Carnahan 1982)
Ts=
T (K )
1+(lT (K)a) ln e(2)
where l=wavelength of emitted radiance (for which the peak response and theaverage of the limiting wavelengths (l=115 mm) (Markham and Barker 1985)will be used) a=hcK (1438times10 Otilde 2 mK) K=Stefan Boltzmannrsquos constant(138times10Otilde 23 J K Otilde 1) h=Planckrsquos constant (626times10Otilde 34 J s) and c=velocity of light(2998times108 s Otilde 1)
In examining the spatial relationship between land usecover types and the surfaceenergy response as measured by Ts the classi ed land cover images in 1989 and1997 were overlaid to the Ts image of corresponding years Because normalizeddiVerence vegetation index (NDVI) has been found to be a good indicator of surfaceradiant temperature (Nemani and Running 1989 Gallo et al 1993b Gillies andCarlson 1995 Lo et al 1997) a NDVI image was computed for 1989 and 1997 fromvisible (063ndash069 mm) and near-infrared (076ndash090 mm) data of the Landsat TMusing the following formula
NDVI=TM4 shy TM3TM4+TM3
(3)
The resultant NDVI image was overlaid with the Ts
image for each year In thisway the interactions among land usecover NDVI and surface temperature can berevealed
Surface temperature change image between 1989 and 1997 was also producedusing image diVerencing This image was overlaid with the land usecover changemap and with the NDVI change map to study how all these changes have interacted
4 Results and discussion41 Urban expansion in the Zhujiang Delta 1989ndash1997
The overall accuracy of the land usecover map for 1989 and 1997 were deter-mined to be 9057 and 8543 respectively (tables 1 and 2) The Kappa indicesfor the 1989 and 1997 maps were 08905 and 08317 respectively Clearly these datahave reasonably high accuracy and thus are suYcient for urban growth detection
Table 3 shows the land use and land cover change matrix of the Zhujiang Deltafrom 1989 to 1997 From this table it is clear that there has been a considerablechange (1282 of the total area) in land use and land cover in the study area duringthe 8-year period Urban or built-up land and horticulture farms have increased inarea (by 4768 and 8866 respectively) and cropland has decreased in area (by4837 )
The overlay of the 1989 and 1997 land usecover map further indicates that ofthe 4768 (65 690 ha) increase in urban or built-up land most results from cropland(3792 ) and horticulture farms (1605 ) Figure 3 shows the areal extent andspatial occurrence of the urban expansion The overlay of this map with a cityndashcounty mask reveals the spatial occurrence of urban expansion within administrativeregions Table 4 shows that in absolute term the greatest urban expansion occurredin Dongguan (23 47890 ha) Baoan (14 94108 ha) Nanhai (80041 ha) and Zhuhai(586971 ha) However in percentage terms the largest increase in urban or built-upland occurred in Zhuhai (110000 ) followed by Shenzhen (30665 ) Baoan
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2003
extracted images were then overlaid and recoded to obtain an urban land change(expansion) image
The urban expansion image was further overlaid with several geographic referenceimages to help analyse the patterns of urban expansion including an image of thecountycity boundary major roads and major urban centres These layers wereconstructed in a vector GIS environment and converted into a raster format (gridsize=30 m) The countycity boundary image can be utilized to nd urban landchange information within each countycity Because proximity to a certain objectsuch as major roads has an important implication in urban land development urbanexpansion processes often show an intimate relationship with distance from thesegeographic objects Using the buVer function in GIS a buVer image was generatedshowing the proximity to the major roads of the study area Ten buVer zones werecreated around a major road with a width of 500 m Local conditions have beentaken into account in selecting these buVer widths The buVer image was overlaidwith the urban expansion image to calculate the amount of urban expansion in eachzone The density of urban expansion was then calculated by dividing the amountof urban expansion by the total amount of land in each buVer zone These valuesof density can be used to construct a distance decay function of urban expansion
32 Urbanization expansion impact analysisUrban development usually gives rise to a dramatic change of the Earthrsquos surface
as natural vegetation is removed and replaced by non-evaporating and non-transpiring surfaces such as metal asphalt and concrete This alteration will inevitablyresult in the redistribution of incoming solar radiation and induce the urbanndashruralcontrast in surface radiance and air temperature The diVerence in ambient airtemperature between an urban and its surrounding rural area is known as the eVectof UHI Given the relationship between surface radiant temperature and the textureof land cover the impact of urban development on surface temperature in theZhujiang Delta can be assessed
Studies on surface temperature characteristics of urban areas using satelliteremote sensing data have been conducted primarily using NOAA AVHRR data(Kidder and Wu 1987 Balling and Brazell 1988 Roth et al 1989 Gallo et al 1993a)The 11 km spatial resolution of these data are found suitable only for small-scaleurban temperature mapping The much higher resolution (120 m) Landsat TMthermal infrared data were seldom used to derive surface temperature RecentlyCarnahan and Larson (1990) have used the TM thermal infrared data to observemesoscale temperature diVerences between urban and rural areas in Indianapoliswhile Nichol (1994) used it to monitor microclimate for some housing estates inSingapore However no research has yet attempted to detect urban-induced surfacetemperature change over time at a local level using multidate TM thermal infrareddata
To measure the surface temperature change from 1989 to 1997 surface radianttemperatures were derived from radiometrically corrected TM thermal infrared data(band 6) using the following quadratic model to convert the digital number (DN)into radiant temperatures (Malaret et al 1985 )
T (K)=209831+0834 DN shy 000133 DN2 (1)
Then corrections for emissivity (e) were applied to the radiant temperatures accordingto the nature of land cover In general vegetated areas were given a value of 095
Q Weng2004
and non-vegetated areas 092 (Nichol 1994) The emissivity corrected surface temper-ature can be computed as follows (Artis and Carnahan 1982)
Ts=
T (K )
1+(lT (K)a) ln e(2)
where l=wavelength of emitted radiance (for which the peak response and theaverage of the limiting wavelengths (l=115 mm) (Markham and Barker 1985)will be used) a=hcK (1438times10 Otilde 2 mK) K=Stefan Boltzmannrsquos constant(138times10Otilde 23 J K Otilde 1) h=Planckrsquos constant (626times10Otilde 34 J s) and c=velocity of light(2998times108 s Otilde 1)
In examining the spatial relationship between land usecover types and the surfaceenergy response as measured by Ts the classi ed land cover images in 1989 and1997 were overlaid to the Ts image of corresponding years Because normalizeddiVerence vegetation index (NDVI) has been found to be a good indicator of surfaceradiant temperature (Nemani and Running 1989 Gallo et al 1993b Gillies andCarlson 1995 Lo et al 1997) a NDVI image was computed for 1989 and 1997 fromvisible (063ndash069 mm) and near-infrared (076ndash090 mm) data of the Landsat TMusing the following formula
NDVI=TM4 shy TM3TM4+TM3
(3)
The resultant NDVI image was overlaid with the Ts
image for each year In thisway the interactions among land usecover NDVI and surface temperature can berevealed
Surface temperature change image between 1989 and 1997 was also producedusing image diVerencing This image was overlaid with the land usecover changemap and with the NDVI change map to study how all these changes have interacted
4 Results and discussion41 Urban expansion in the Zhujiang Delta 1989ndash1997
The overall accuracy of the land usecover map for 1989 and 1997 were deter-mined to be 9057 and 8543 respectively (tables 1 and 2) The Kappa indicesfor the 1989 and 1997 maps were 08905 and 08317 respectively Clearly these datahave reasonably high accuracy and thus are suYcient for urban growth detection
Table 3 shows the land use and land cover change matrix of the Zhujiang Deltafrom 1989 to 1997 From this table it is clear that there has been a considerablechange (1282 of the total area) in land use and land cover in the study area duringthe 8-year period Urban or built-up land and horticulture farms have increased inarea (by 4768 and 8866 respectively) and cropland has decreased in area (by4837 )
The overlay of the 1989 and 1997 land usecover map further indicates that ofthe 4768 (65 690 ha) increase in urban or built-up land most results from cropland(3792 ) and horticulture farms (1605 ) Figure 3 shows the areal extent andspatial occurrence of the urban expansion The overlay of this map with a cityndashcounty mask reveals the spatial occurrence of urban expansion within administrativeregions Table 4 shows that in absolute term the greatest urban expansion occurredin Dongguan (23 47890 ha) Baoan (14 94108 ha) Nanhai (80041 ha) and Zhuhai(586971 ha) However in percentage terms the largest increase in urban or built-upland occurred in Zhuhai (110000 ) followed by Shenzhen (30665 ) Baoan
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2004
and non-vegetated areas 092 (Nichol 1994) The emissivity corrected surface temper-ature can be computed as follows (Artis and Carnahan 1982)
Ts=
T (K )
1+(lT (K)a) ln e(2)
where l=wavelength of emitted radiance (for which the peak response and theaverage of the limiting wavelengths (l=115 mm) (Markham and Barker 1985)will be used) a=hcK (1438times10 Otilde 2 mK) K=Stefan Boltzmannrsquos constant(138times10Otilde 23 J K Otilde 1) h=Planckrsquos constant (626times10Otilde 34 J s) and c=velocity of light(2998times108 s Otilde 1)
In examining the spatial relationship between land usecover types and the surfaceenergy response as measured by Ts the classi ed land cover images in 1989 and1997 were overlaid to the Ts image of corresponding years Because normalizeddiVerence vegetation index (NDVI) has been found to be a good indicator of surfaceradiant temperature (Nemani and Running 1989 Gallo et al 1993b Gillies andCarlson 1995 Lo et al 1997) a NDVI image was computed for 1989 and 1997 fromvisible (063ndash069 mm) and near-infrared (076ndash090 mm) data of the Landsat TMusing the following formula
NDVI=TM4 shy TM3TM4+TM3
(3)
The resultant NDVI image was overlaid with the Ts
image for each year In thisway the interactions among land usecover NDVI and surface temperature can berevealed
Surface temperature change image between 1989 and 1997 was also producedusing image diVerencing This image was overlaid with the land usecover changemap and with the NDVI change map to study how all these changes have interacted
4 Results and discussion41 Urban expansion in the Zhujiang Delta 1989ndash1997
The overall accuracy of the land usecover map for 1989 and 1997 were deter-mined to be 9057 and 8543 respectively (tables 1 and 2) The Kappa indicesfor the 1989 and 1997 maps were 08905 and 08317 respectively Clearly these datahave reasonably high accuracy and thus are suYcient for urban growth detection
Table 3 shows the land use and land cover change matrix of the Zhujiang Deltafrom 1989 to 1997 From this table it is clear that there has been a considerablechange (1282 of the total area) in land use and land cover in the study area duringthe 8-year period Urban or built-up land and horticulture farms have increased inarea (by 4768 and 8866 respectively) and cropland has decreased in area (by4837 )
The overlay of the 1989 and 1997 land usecover map further indicates that ofthe 4768 (65 690 ha) increase in urban or built-up land most results from cropland(3792 ) and horticulture farms (1605 ) Figure 3 shows the areal extent andspatial occurrence of the urban expansion The overlay of this map with a cityndashcounty mask reveals the spatial occurrence of urban expansion within administrativeregions Table 4 shows that in absolute term the greatest urban expansion occurredin Dongguan (23 47890 ha) Baoan (14 94108 ha) Nanhai (80041 ha) and Zhuhai(586971 ha) However in percentage terms the largest increase in urban or built-upland occurred in Zhuhai (110000 ) followed by Shenzhen (30665 ) Baoan
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2005
Table 1 Error matrix of the land use and land cover map 1989
Reference dataClassi eddata UC UB BL CR HF DP FO WA RT CT PA ( ) UA ( )
UC Unclassi ed UB urban or built-up land BL barren land CR crop land HFhorticulture farm DP dikendashpond land FO forest WA water
RT Reference total CT classi ed total PA producerrsquos accuracy UA userrsquos accuracy
(23333 ) and Dongguan (12571 ) Massive urban sprawl in these areas can beascribable to rural urbanization which is a common phenomenon in the post-reformChina Rapid urban development in the form of small towns in the east side of thedelta is highly in uenced by the investment from Hong Kong (Yeh and Li 1996) Incontrast those old cities such as Guangzhou and Foshan do not show a rapidincrease in urban or built-up land because they have no land to expand further (asthey have already expanded fully in the past) and the concentration of urbanenterprises in the city proper Shenzhen and Zhuhai were designated as SpecialEconomic Zones at the same time but the pace of urbanization in the two cities isquite diVerent Urban development in Shenzhen has mostly been completed in the
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2006
Tab
le3
Lan
dus
eco
ver
chan
gem
atri
x19
89ndash1
997
(ha)
1997
Urb
anor
Bar
ren
Hor
ticu
ltur
eD
ike-
pond
1989
Unc
lass
ied
built
-up
land
Cro
plan
dfa
rms
land
For
est
Wat
er19
89T
otal
Unc
lass
ied
391
824
00
00
00
00
391
824
0U
rban
orbu
ilt-u
p0
5418
949
338
208
908
3581
68
1588
74
3082
77
7407
36
1377
68B
arre
nla
nd0
1160
34
661
7741
560
286
904
1285
47
1414
53
1293
75
2910
54
Cro
plan
d0
7715
15
4651
11
152
400
215
536
5527
27
4449
71
2925
84
578
767
Hor
ticu
ltur
efa
rms
032
660
837
752
344
972
913
237
212
850
243
752
382
222
227
860
5D
ikendash
pond
land
014
902
832
103
3393
14
2023
86
4248
97
2640
96
3132
74
145
852
For
est
083
786
430
285
926
294
710
258
939
067
212
804
854
368
127
768
3W
ater
045
713
747
295
1615
66
1036
61
1117
97
1845
09
6441
43
109
006
1997
Tot
al3
918
240
203
458
1340
41
2988
0352
560
914
287
222
528
114
736
05
475
026
88C
hang
e(h
a)0
6569
0shy
1570
13
shy27
996
424
700
4shy
2980
shy52
402
3835
470
209
53
Cha
nge
()
0+
476
8shy
539
3shy
483
7+
886
6shy
002
shy18
87
+3
1912
82
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2007
Figure 3 A map or urban expansion in the Zhujiang Delta 1989ndash1997
1980s while Zhuhairsquos urban expansion appears primarily during the period of1989ndash1997 (586971 ha)
Urban expansion processes in the Zhujiang Delta during the period of 1989 to1997 are further examined by plotting a distance decay curve from a major roadand establishing a mathematical equation The result indicates that the density ofurban expansion decreases as the distance increases away from a major road Mosturban expansion (66 ) can be observed within a distance of 2000 m from a majorroad This rapid urban expansion pattern is vividly illustrated along the superhigh-way from Guangzhou to Hong Kong as seen in gure 3 where Hong Kong investorsseek sites for constructing factories and housing The relationship between the densityof urban expansion (Y ) and the distance from a major road (X ) can be mathematicallyexpressed as
Y=02237 e Otilde 000046x (4)
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2008
Figure 4 Spatial distribution of temperature increase zones 1989ndash1997
42 Urbanization impact on surface temperature421 Thermal signatures of land cover types
In order to understand the impacts of land usecover change on surface radianttemperature the characteristics of the thermal signatures of each land cover typemust be studied rst The average values of radiant surface temperatures by landcover type in 1989 and 1997 are summarized in table 5 It is clear that for bothyears urban or built-up land exhibits the highest surface radiant temperature(33630 K in 1989 and 33914 K in 1997) followed by barren land (33552 K in 1989and 33836 K in 1997) This implies that urban development does bring up surfaceradiant temperature by replacing natural vegetation with non-evaporating non-transpiring surfaces such as stone metal and concrete The standard deviations ofthe radiant temperature values are small for both land cover types indicating thaturban surfaces do not experience a wide variation in surface radiant temperaturebecause of the dry nature of non-evapotranspirativ e urban materials The lowestradiant temperature in 1989 is observed in forest (30883 K) followed by waterbodies (30976 K) dikendashpond land (31239 K) and cropland (31436 K) This pattern
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2009
Table 4 Satellite-detected urban expansion in the Zhujiang Delta 1989ndash1997
Urban area 1989 Urban area 1997 Change ChangeCitycounty (ha) (ha) (ha) ( )
Table 5 Average surface temperature in degrees Kelvin by land cover type
Standard StandardLand cover 1989 deviation (plusmn) 1997 deviation (plusmn)
Urban or built-up land 33630 727 33914 838Barren land 33552 657 33836 680Cropland 31436 914 31663 1102Horticulture farms 31560 1490 31784 1503Dikendashpond land 31239 470 31483 485Forest 30883 1064 31291 1029Water 30976 937 31105 1004
is in contrast with that in 1997 when the low radiant temperature is found in waterbodies (31105 K) followed by forest (31291 K) dikendashpond land (31483 K) andcropland (31663 K) This diVerent pattern is primarily attributed to the diVerencesin solar illumination the state of vegetation and atmospheric in uences on theremotely sensed TM dataset The 1989 image was taken in winter (13 December)while the 1997 image in summer (27 August) The diVerence in data acquisitionseason is clearly re ected in the surface radiant temperatures of water bodies Theradiant temperature of water bodies is higher than that of forest by 083 K in winterwhile in summer lower than that of forest by 186 K Because of distinctive character-istics of rivers lakes and oceans their radiant temperature values vary Rivers(31512 K) and lakes (31433 K) register a much higher temperature than oceans(29180 K) in 1997 Rivers and lakes often have a higher silt content than oceansThis diVerence probably also has something to do with the increasingly serious waterpollution problem in the Zhujiang Delta where the waste water resulting from sugarre ning paper pulp processing textile dyeing and electroplating is often directlyreleased into rivers (Lin 1997) Forests show a considerably low radiant temperaturein both years because dense vegetation can reduce amount of heat stored in the soiland surface structures through transpiration However forests show a relatively largestandard deviation in radiant temperature values (937 K in 1989 and 1004 K in
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2010
1997) compared with other land cover types indicating the heterogeneous nature oftree covers Cropland horticulture farms and dikendashpond land tend to have a sparsevegetation and exposed bared soil The in uence of surface soil water content andvegetation contribute to a broad variation in their surface radiant temperature value
Given the relationship between surface radiant temperature and the texture ofland cover that is in uenced by land use changes in land use and land cover canhave a profound eVect on the surface radiant temperature in a region GIS coupledwith image processing can help one to visualize the impact of land use and landcover change on surface radiant temperature The technique of image diVerencing isemployed to produce a radiant temperature change image after the surface radianttemperature of each year has been normalized This image is then overlaid with theimages of urban expansion The results of GIS analysis show that the urban develop-ment between 1989 and 1997 has given rise to an average increase of 1301 deg K insurface radiant temperature with a standard deviation of plusmn1060 deg K It shouldbe noted that this number of increase could be applied to changed areas only
422 Relationship between radiant surface temperature and NDVIThe relationship between surface radiance temperature and NDVI was investi-
gated for each land cover type through correlation analysis (pixel by pixel) Table 6shows the Pearsonrsquos correlation coeYcients between the two elements in 1989 and1997 The signi cance of each correlation coeYcient was determined using a one-tail Studentrsquos t-test It is apparent from table 6 that surface radiance temperaturevalues tend to negatively correlate with NDVI values for all land cover types inboth years The highest negative correlation was found in forest (shy 08539) and urbanor built-up land (shy 07731) in 1989 and in urban or built-up land (shy 09495 ) andforest (shy 08897) in 1997 In both years horticulture farms exhibit a very signi cantcorrelation (shy 07569 for 1989 and shy 07966 for 1997) An even lower correlationwas observed in construction sites of both years (shy 04549 and shy 03375)
The strong negative correlation between surface radiance temperature and NDVIimplies that the higher biomass a land cover has the lower the surface temperatureBecause of this relationship between surface radiance temperature and NDVIchanges in land usecover have an indirect impact on surface temperatures throughNDVI The values of NDVI in each year were scaled according to the followingformula (Gillies et al 1997) because the absolute values of NDVI tend to varytemporally in a non-systematic manner (Price 1987 Che and Price 1992)
N=NDVI shy NDVIoNDVIs shy NDVIo
(5)
Table 6 Pearsonrsquos correlation coeYcients between average surface temperature in degreesKelvin and NDVI by land cover type (signi cant at 005 level )
Land cover 1989 1997
Urban or built-up land shy 07731 shy 09495Barren land shy 04549 shy 03375Cropland shy 06320 shy 00971Horticulture farms shy 07569 shy 07966Dikendashpond land shy 02756 shy 02588Forest shy 08539 shy 08897Water shy 01921 shy 01784
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2011
where NDVIo is the minimum value and NDVIs the maximum value of NDVI inan image Usually NDVIo is associated with lsquowaterrsquo while NDVIs is associated withlsquoforestrsquo Image diVerencing was then performed between the 1997 and 1987 NDVIimages GIS analysis indicates that the scaled NDVI value decreased 011 between1989 and 1997 in the urbanized areas
423 Spatial distribution of surface radiant temperatureThe impact of land use and cover changes on surface radiant temperature can
also be examined spatially The surface temperature change image obtained by imagediVerencing is recoded into eight temperature zones based on the classi cationscheme of equal interval Zones 7 and 8 have a positive value of temperature changeindicating a temperature increase between 1989 and 1997 while others have anegative value The mapped patterns of temperature change exhibit distinctly diVerentspatial patterns among the eight temperature zones A query regarding the arealextent and spatial occurrence of each zone indicates that the spatial pattern of zone8 (Temperature increase=2425ndash485 K) ( gure 4) coincides with that of urban expan-sion A GIS analysis using buVer and overlay functions was conducted to acquirethe density of temperature zone 8 in each 500 m buVer zone away from major roadsThe result shows a tendency toward decreasing densities as distance increases fromroads A correlation analysis between the density of temperature zone 8 and that ofurban expansion gives a multiple r value of 06310 (signi cant at 005 level) thusleading to the conclusion that urban expansion is conducive to the increase in surfaceradiant temperature
5 Discussions and conclusionsIn this study an integrated approach of remote sensing and GIS was developed
for evaluation of rapid urban expansion and its impact on surface temperature inthe Zhujiang Delta China Results revealed a notable increase in urban landusecover between 1989 and 1997 Urban land development was uneven in diVerentparts of the delta and the density of urban expansion showed a tendency of declineas the distance increased away from a major road
The combined use of remote sensing and GIS allows for an examination of theimpact of urban expansion on surface temperature The results showed that urbanland development raised surface radiant temperature by 1301 K This study has alsodemonstrated that the direct eVect of urban land usecover change on one environ-mental element can cause indirect eVect on the other The increase of surface radianttemperature was related to the decrease of biomass
The spatial pattern of radiant temperature increase was correlated with thepattern of urban expansion This is particularly true when all these patterns werereferenced to major roads
The integration of remote sensing and GIS provides an eYcient way to detecturban expansion and to evaluate its impact on surface temperature The digitalimage classi cation coupled with GIS has demonstrated its ability to provide compre-hensive information on the nature rate and location of urban land expansionBiophysical measurements including surface radiant temperature and biomass canbe extracted from Landsat TM images Using the technique of image diVerencingthe environmental changes over time can be evaluated To examine the environmentalimpact of urban expansion the mapped patterns of environmental changes can belinked to urban expansion pattern by correlation analysis
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
Q Weng2012
The environmental impacts of land use and land cover change can be modelledat local level using the integrated approach of remote sensing and GIS The methodo-logy employed in this study provides an alternative to the traditional empiricalobservation and analysis using in situ ( eld) data for environmental studies Thismethodology should be possible to apply to other regions in China or in othernations that undergo a rapid urbanization Future modelling eVorts should test thepossibility and feasibility that an integrated approach of remote sensing and GIScan be applied to investigate regional and global environmental impacts of land useand land cover change
However in applying the methodology used in this paper and the above ndsthe following two points must be borne in mind First the computed surface radianttemperatures may be higher than as they were since the eVects of surface roughnesson surface temperature have not been taken into account Several authors (Kimes1983 Cassels et al 1992a b) have elaborated this issue and suggest scrutinizing thetemperatures of each part of the vegetationndashground system (such as shaded groundsunny ground shade vegetation and sunny vegetation) and examining the eVects ofdiVerent canopy structures EVective land surface temperature can be derived onlyafter its relationship to the component temperatures has been mathematically mod-elled Secondly a more complicated emissivity correction scheme that diVerentiatesseven types of land covers should be applied in any further study EVective measure-ment of surface temperatures requests to analyse the signi cance of the nature ofsurface and its roughness on emissivities
AcknowledgmentsThe author is grateful to Dr Chor Pang Lo for his help and suggestions on an
early version of this paper The funded support of the National Geographic Societywhich made my eldwork possible is also greatly acknowledged Last but not leastthe author wishes to thank anonymous reviewers for their useful comments andsuggestions
ReferencesArtis D A and Carnahan W H 1982 Survey of emissivity variability in thermography
of urban areas Remote Sensing of Environment 12 313ndash329Balling R C and Brazell S W 1988 High resolution surface temperature patterns in a
complex urban terrain Photogrammetric Engineering and Remote Sensing 541289ndash1293
Carnahan W H and Larson R C 1990 An analysis of an urban heat sink RemoteSensing of Environment 33 65ndash71
Cassels V Sobrino J A and Coll C 1992a On the use of satellite thermal data fordetermining evapotranspiration in partially vegetated areas International Journal ofRemote Sensing 13 2669ndash2682
Cassels V Sobrino J A and Coll C 1992b A physical model for interpreting the landsurface temperature obtained by remote sensors over incomplete canopies RemoteSensing of Environment 39 203ndash211
Che N and Price J C 1992 Survey of radiometric calibration results and methods forvisible and near infrared channels of NOAA-7 -9 and -11 AVHRRs Remote Sensingof Environment 50 1ndash7
Department of Geography Zhongshan University 1988 The Land and Water Resourcesin the Zhujiang Delta (Guangzhou Zhongshan University Press)
Ditu Chubanshe 1977 Provincial Atlas of the Peoplersquos Republic of China (Beijing PeoplersquosPress)
Ehlers M Jadkowski M A Howard R R and Brostuen D E 1990 Application of
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion 2013
SPOT data for regional growth analysis and local planning PhotogrammetricEngineering and Remote Sensing 56 175ndash180
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993a The use of NOAA AVHRR data for assessment of the urban heat island eVectJournal of Applied Meteorology 32 899ndash908
Gallo K P McNab A L Karl T R Brown J F Hood J J and Tarpley J D1993b The use of a vegetation index for assessment of the urban heat island eVectInternational Journal of Remote Sensing 14 2223ndash2230
Gillies R R and Carlson T N 1995 Thermal remote sensing of surface soil water contentwith partial vegetation cover for incorporation into climate models Journal of AppliedMeteorology 34 745ndash756
Gillies R R Carlson T N Cui J Kustas W P and Humes K S 1997 A veri cationof the lsquotrianglersquo method for obtaining surface soil water content and energy uxesfrom remote measurements of the Normalized DiVerence Vegetation index (NDVI)and surface radiant temperature International Journal of Remote Sensing 183145ndash3166
Gong Z and Chen Z 1964 The soils of the Zhujiang River Delta Journal of Soils 3669ndash124 (in Chinese)
Harris P M and Ventura S J 1995 The integration of geographic data with remotelysensed imagery to improve classi cation in an urban area PhotogrammetricEngineering and Remote Sensing 61 993ndash998
Jensen J R 1996 Introductory Digital Image Processing A Remote Sensing Perspective2nd edn (Upper Saddle River NJ Prentice Hall)
Kidder S Q and Wu H T 1987 A multispectral study of the St Louis area under snow-covered conditions using NOAA-7 AVHRR data Remote Sensing of Environment22 159ndash172
Kimes D J 1983 Remote sensing of row crop structure and component temperatures usingdirectional radiometric temperatures and inversion techniques Remote Sensing ofEnvironment 13 33ndash55
Lin G C S 1997 Transformation of a rural economy in the Zhujiang Delta China Quarterly149 56ndash80
Lo C P 1989 Recent spatial restructuring in Zhujiang Delta South China a study ofsocialist regional development strategy Annals of the Association of the AmericanGeographers 79 293ndash308
Lo C P Quattrochi D A and Luvall J C 1997 Application of high-resolution thermalinfrared remote sensing and GIS to assess the urban heat island eVect InternationalJournal of Remote Sensing 18 287ndash304
Malaret E Bartolucci L A Lozano D F Anuta P E and McGillem C D 1985Landsat-4 and Landsat-5 Thematic Mapper data quality analysis PhotogrammetricEngineering and Remote Sensing 51 1407ndash1416
Markham B L and Barker J K 1985 Spectral characteristics of the LANDSAT ThematicMapper sensors International Journal of Remote Sensing 6 697ndash716
Mather A S 1986 Land Use (London Longman)Nemani R R and Running S W 1989 Estimation of regional surface resistance to
evapotranspiration from NDVI and thermal-IR AVHRR data Journal of AppliedMeteorology 28 276ndash284
Nichol J E 1994 A GIS-based approach to microclimate monitoring in Singaporersquos high-rise housing estates Photogrammetric Engineering and Remote Sensing 60 1225ndash1232
Price J C 1987 Calibration of satellite radiometers and the comparison of vegetationindices Remote Sensing of Environment 21 15ndash27
Roth M Oke T R and Emery W J 1989 Satellite derived urban heat islands from threecoastal cities and the utilisation of such data in urban climatology InternationalJournal of Remote Sensing 10 1699ndash1720
Ruddle K and Zhong G 1988 Integrated AgriculturendashAquaculture in South China theDikendashPond System of the Zhujiang Delta (Cambridge Cambridge University Press)
Steffen W L Walker B H Ingram J S and Koch G W 1992 Global change andterrestrial ecosystems the operational plan IGBP Report No 21 InternationalGeospherendashBiosphere Programme Stockholm
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
A remote sensingndashGIS evaluation of urban expansion2014
Treitz P M Howard P J and Gong P 1992 Application of satellite and GIS technologiesfor land-cover and land-use mapping at the rural-urban fringe a case studyPhotogrammetric Engineering and Remote Sensing 58 439ndash448
Weng Q 1998 Local impacts of the post-Mao development strategy the case of the ZhujiangDelta southern China International Journal of Urban and Regional Studies 22425ndash442
Yeh A G O and Li X 1996 Urban growth management in the Pear River deltamdashanintegrated remote sensing and GIS approach ITC Journal 1 77ndash85
Zhong G 1980 The mulberry dike- sh pond system in the Zhujinag Delta a man-madeecosystem of landndashwater interaction Acta Geographica Sinica 35 200ndash212
