Modeling the Spatiotemporal Distribution
of Agricultural-Feasible Land in China
Fei Carnes
Center for Geographic Analysis, Harvard University
Weihe Wendy Guan [email protected]
Kang Wu [email protected]
Fei Carnes [email protected]
2016 ESRI USER CONFERENCE
mailto:[email protected]:[email protected]:[email protected]
Research Questions:
• Where are agricultural-feasible lands in China?
• How feasible to agriculture the land is naturally, in different parts of China?
• Where are lands lost to urbanization in the recent decades?
• How feasible these urban-claimed lands are to agriculture?
• How severe this lose is in different parts of China, over the recent decades?
Datasets Used for Agricultural Feasibility Analysis
Model factors Variables Data Source Source Data Year
Climate
Accumulated
temperature ≥10℃CAS 1981-1990 average
Sunshine hours CAAS 1991-2000 average
Hydrology
Annual rainfall (ml) CAS 1991-2000 average
Distance to rivers (m)USGS (derived from
River vectors)-
Soil
Soil PH FAO GeoNetwork 2007
Soil depth (cm) FAO GeoNetwork 2007
Soil moisture storage
capacity (mm/m)FAO GeoNetwork 2007
Topography
Elevation USGS -
SlopeUSGS (derived from
Elevation raster)-
Derived data layers and fuzzy variables weight for
agricultural feasibility analysis
Factors Weight1 Fuzzy variables Weight2
Hydrology 0.3Fuzzy annual rainfall 1
Fuzzy distance to rivers 0.4
Climate 0.3Fuzzy accumulated temperature ≥10℃ 0.75
Fuzzy sunshine hours 0.25
Soil 0.2
Fuzzy soil PH 0.2
Fuzzy soil Depth 0.4
Fuzzy soil Moisture Storage Capacity 0.4
Topography 0.2Fuzzy elevation 0.25
Fuzzy slope 0.75
Fuzzy methods for continuous data
Annual
Precipitation
Accumulated
Temperature>=10°C
Elevation SlopeDistance to River
within 30,000 metersSunshine Hour
Sigmoidal
increasing
0 1500ml
FuzzyLarge
0 30,000m
Linear
0 max
Linear
Fuzzy
Precipitation
Fuzzy
Temperature
Fuzzy
ElevationFuzzy
SlopeFuzzy
Distance to River
Fuzzy
Sunshine hour
2400 °C (midpoint)
0.5
-153 7227m
Sigmoidal decreasing
15 (midpoint)
FuzzySmall
0.5
Fuzzy methods for categorical data
Soil
DepthSoil Moisture Storage Capacity
Fuzzy Soil PH Fuzzy Soil Moisture Storage Capacity
8.5
Non-soil (water, Rock..)
[4.5, 5.5) or [7.2,8.5)
0.2
0.5
0
[5.5, 7.2] 1
Old Values New Values
Fuzzy Soil Depth
Shallow (10-50cm)
Very shallow (
Agricultural feasibility indexes across China
Version 4 DMSP-OLS Nighttime Lights Time Series
Average Visible, Stable Lights, & Cloud Free Coverages
Year\Sat. F10 F12 F14 F15 F16 F18
1992 F101992 ------- ------- ------- ------- -------
1993 F101993 ------- ------- ------- ------- -------
1994 F101994 F121994 ------- ------- ------- -------
1995 ------- F121995 ------- ------- ------- -------
1996 ------- F121996 ------- ------- ------- -------
1997 ------- F121997 F141997 ------- ------- -------
1998 ------- F121998 F141998 ------- ------- -------
1999 ------- F121999 F141999 ------- ------- -------
2000 ------- ------- F142000 F152000 ------- -------
2001 ------- ------- F142001 F152001 ------- -------
2002 ------- ------- F142002 F152002 ------- -------
2003 ------- ------- F142003 F152003 ------- -------
2004 ------- ------- ------- F152004 F162004 -------
2005 ------- ------- ------- F152005 F162005 -------
2006 ------- ------- ------- F152006 F162006 -------
2007 ------- ------- ------- F152007 F162007 -------
2008 ------- ------- ------- ------- F162008 -------
2009 ------- ------- ------- ------- F162009 -------
2010 ------- ------- ------- ------- ------- F182010
2011 ------- ------- ------- ------- ------- F182011
2012 ------- ------- ------- ------- ------- F182012
2013 ------- ------- ------- ------- ------- F182013
South of Beijing where night
light pixel value equals 9 in 2013
Southwest of Beijing where night
light pixel value equals 20 in 2013
South of Beijing where night light
pixel value equals 32 in 2013
West of Tianjin where night light
pixel value equals 41 in 2013
Southwest of Tianjin where night
light pixel value equals 50 in 2013
Night light pixel values as indications of percentage of
constructed land cover
Pixel Value % Land Constructed
0-5 0
5-10 10
10-15 20
15-20 30
20-25 40
25-30 50
30-35 60
35-40 70
40-45 80
45-50 90
50-63 100
Reclassification of the agricultural feasibility index
values into 11 integer
From To New
0.144929662 0.216596265 0
0.216596265 0.288262867 1
0.288262867 0.359929469 2
0.359929469 0.431596072 3
0.431596072 0.503262674 4
0.503262674 0.574929277 5
0.574929277 0.646595879 6
0.646595879 0.718262481 7
0.718262481 0.789929084 8
0.789929084 0.861595686 9
0.861595686 0.933262289 10
The change in number of pixels
belonging to each combination of
night light brightness and agricultural
feasibility class between 1992 and
2013.
From To New
0 5 10
5 10 9
10 15 8
15 20 7
20 25 6
25 30 5
30 35 4
35 40 3
40 45 2
45 50 1
50 63 0
Reclassification of night light brightness into parts
per tenth of non-constructed land
Agriculture Potentials in 1992
Agriculture Potentials in 2002
Agriculture Potentials in 2013
Country-wide summary of pixel values from the agricultural
potentials layers
Losses of Agriculture Potentials between 1992 and 2013
Province From_Year To_Year Count Min Mas Range Mean STD Sum Variety Majority Minority Mediam
Shanghai 1992 2013 4802 0 90 90 46.8155 26.5263 224808 26 72 48 54
Jiangsu 1992 2013 105452 -9 100 109 25.6562 25.3732 2705501 39 9 25 16
Tianjin 1992 2013 12092 -7 70 77 22.6532 18.7344 273922 18 7 36 14
Zhejiang 1992 2013 101003 -10 100 110 16.3282 25.4416 1649194 32 0 35 0
Beijing 1992 2013 17628 -28 63 91 13.9859 18.6537 246543 27 0 -28 6
Shandong 1992 2013 157498 -49 80 129 13.3835 14.9683 2107878 43 7 -49 7
Guangdong 1992 2013 176268 -30 100 130 11.9757 20.6134 2110934 25 0 -30 0
Taiwan 1992 2013 32631 -45 81 126 10.3790 16.0567 338676 42 0 -32 0
Anhui 1992 2013 150868 -20 100 120 8.8347 16.2665 1332875 41 0 -20 0
Henan 1992 2013 178096 -36 90 126 8.5545 12.8528 1523514 57 0 -36 7
Fujian 1992 2013 123530 -60 100 160 7.8114 17.3658 964937 31 0 -60 0
Hebei 1992 2013 200022 -48 70 118 7.1837 11.6813 1436906 46 0 -4 0
Hainan 1992 2013 31719 -63 100 163 6.4025 13.7842 203080 33 0 -50 0
Chongqing 1992 2013 88703 -27 90 117 4.7235 13.5144 418987 33 0 80 0
Hubei 1992 2013 200091 -56 100 156 4.6597 12.2978 932361 49 0 -56 0
Liaoning 1992 2013 149214 -35 72 107 4.4500 10.0128 664007 38 0 15 0
Shanxi 1992 2013 168294 -70 70 140 4.4219 9.9627 744175 52 0 -63 0
Hongkong 1992 2013 98 -10 40 50 4.2857 8.6897 420 6 0 -10 0
Jiangxi 1992 2013 179708 -30 100 130 3.9930 12.5034 717577 42 0 -27 0
Shaanxi 1992 2013 221524 -28 72 100 3.7333 9.6264 827010 44 0 50 0
Hunan 1992 2013 228143 -60 100 160 3.6643 11.2766 835987 44 0 -60 0
Ningxia 1992 2013 55823 -35 70 105 3.5491 9.9876 198122 45 0 -35 0
Guangxi 1992 2013 249010 -50 100 150 3.3098 10.0354 824161 35 0 7 0
Guizhou 1992 2013 189283 -56 90 146 2.5015 8.9506 473494 50 0 -27 0
Jilin 1992 2013 201052 -35 72 107 2.4075 7.4854 484027 38 0 -35 0
Yunnan 1992 2013 400232 -63 100 163 2.1435 8.3204 857879 60 0 -63 0
Heilongjiang 1992 2013 477205 -35 70 105 2.1043 6.1230 1004167 45 0 -30 0
Sichuan 1992 2013 520460 -45 90 135 1.9169 8.2099 997657 52 0 -5 0
Gansu 1992 2013 435864 -20 70 90 0.8593 4.3509 374528 46 0 27 0
Neimenggu 1992 2013 1215493 -42 70 112 0.6377 4.0490 775095 51 0 -30 0
Xinjiang 1992 2013 1736719 -70 70 140 0.3971 3.3192 689592 65 0 -40 0
Qinghai 1992 2013 770050 -50 60 110 0.1191 1.7436 91701 47 0 -50 0
Xizang 1992 2013 1278149 -8 50 58 0.0215 0.6235 27490 33 0 -2 0
Statistical summary of the loss of agriculture potentials
between 1992 and 2013 by provinces
Average Losses of Agriculture Potentials by
Province, 1992-2013
• This study is partially sponsored by:
- The Lee and Juliet Folger Fund,
- Fairbank Center for Chinese Studies, Harvard University, and
- Natural Science Foundation of China (grant No. 41401178).
• Dr. Yu Deng, Visiting Fellow of the Harvard John A. Paulson
School of Engineering and Applied Sciences (2012-2013),
provided the temperature, sunshine and rainfall data from the
Chinese Academy of Sciences.
Acknowledgements
Thanks!
Questions?
Modeling the Spatiotemporal Distribution of
Agricultural-Feasible Land in China
Weihe Wendy Guan [email protected]
Kang Wu [email protected]
Fei Carnes [email protected]
Center for Geographic Analysis, Harvard University
mailto:[email protected]:[email protected]:[email protected]
