Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
*Manjunatha M.C.1, Basavarajappa H.T.2 1Department of Civil Engineering, Maharaja Institute of Technology, Thandavapura, Mysuru-571 302, India 2Department of Studies in Earth Science, Centre for Advanced Studies in Precambrian Geology, University of Mysore, Mysuru-570 006, India
Earth's land use/land cover (LC/LU) classification provides valuable information particularly on natural resources, mapping and its monitoring. There is a significant change on LC/LU across the globe due to the climatic changes, rapid increase in population and over demand of economic natural resources. Remote Sensing (RS) satellite data with its synoptic view and multispectral data provides essential information in proper planning of LU/LC conditions of larger areas. The study aims to map and monitor the existing LU/LC classification scientifically using geospatial tools in database generation, analyses and information extraction. Thematic maps of the study area are prepared using satellite images in conjunction with collateral data Survey of India (SoI) toposheets, forest and wasteland maps. An attempt have been made to delineate the Level-I, Level-II and Level-III LU/LC classification system through NRSC guidelines (2011) using both Digital Image Processing (DIP) and Visual Image Interpretation Techniques (VIIT) by GIS software’s with limited Ground Truth Check (GTC). More accurate classification is observed in case of digital technique as compared to that of visual technique in terms of area statistics. The final results highlight the potentiality of geospatial technique in optimal and sustainable land use planning of natural resource and its management.
LULC classification provides vital inputs required for socio-ecological concerns and optimal use of land resources for the developing countries like India (Sharma et al, 2018). The main resource controlling primary productivity for terrestrial ecosystems can be defined in terms of land: the area of land available, land quality, moisture regime and edaphic character (Sharma et al, 2018). Changes in LU/LC affect global systems or occur in a localized fashion in enough places to have a significant effect (Meyer and Turner, 1992).LU/LC provides a better understanding on the cropping pattern and spatial distribution of fallow lands, forests, grazing lands, wastelands and surface water bodies, which is vital for urban developmental planning and management (Philip and Gupta, 1990). Despite successful substitution of land-based resources with fossil fuels and mineral resources, land remains of prime importance (Darwin et
al., 1996). LU/LC exposes considerable influence on the various hydrological aspects such as interception, infiltration, catchment area, evaporation and surface flow (Sreenivasalu and Vijay Kumar, 2000). Indian Remote Sensing (IRS) has been extensively utilized for Satellite data acquisition at periodic intervals to monitor the land resources and to evaluate the land use/ land cover classification & its impact on natural land resources (NRSA, 1995). The spatial information of agro ecosystem modeling (Lenz-Wiedemann et al, 2010) yields estimation (Vibhute and Gawali, 2013) subsidy control
*Corresponding Author: Manjunatha M.C, Department of Civil Engineering, Maharaja Institute of Technology, Thandavapura, Mysuru-571 302, India. Email: [email protected]
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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(Schmedtmann and Campagnolo, 2015) and retrieval of biophysical plant parameters on regional scales is not sufficient (Zhao et al, 2015). For numerous agricultural applications and differentiate crops is a demanding task, as different crop types have similar reflection properties in remote sensing images for some periods of the year (Waldhoff et al, 2012). Increasing human interventions and unfavorable bio-climatic environment has led to transformation of large tracts of agricultural land into wasteland (Basavarajappa et al, 2019). Due to the lack of appropriate land cover data, many assessments have used models to delimit potential land cover (Alexandratos, 1995). Information describing current land cover is an important input for planning and modeling, but the quality of such data defines the reliability of the simulation outputs (Townshend, 1992). Proper land management and development should be initiated to increase the land productivity, restoration of soil degradation, reclamation of wastelands, and increase in environmental qualities and to meet the needs of rapidly growing population of the country (Manjunatha and Basavarajappa, 2015b). Land use classification is the systematic assessment and alternatives for optimal land use to improve socio-economic conditions (FAO, 2017). Land-use classification at appropriate scales increase their productivity, support sustainable agriculture & food systems, promotes governance over land and water resources and meets the needs of society (FAO, 2017). There are a variety of methods have been introduced for LULC classification with the development and advances in remote sensing technology and satellites (Mishra et al., 2014). Anderson classification system is the most widely used classification
scheme today, consists of multiple levels of classification designed to be compatible with different levels of details (Tammy and James, 2015). It is comprised of a hierarchal grouping of three levels, allowing for applicability at multiple resolutions. Level-I can be used when finer details are not needed, such as for national or regional scales, and is more appropriate for land cover identification. Yet, Level-II and Level-III is available when finer detail is needed at a local scale and can be more readily described as land uses (Tammy and James, 2015). Without a standard classification framework, it is difficult to identify changes occurring over time, compare between places, and to avoid duplication of efforts. STUDY AREA It is located in between 12007’05” to 12027’13” N latitudes and 76027’12” to 76050’10” E longitudes with the general elevation of 770 mts above MSL covering an area of 805.63 km2 (Figure 1). Tourism is the major industry alongside the traditional industries in Mysuru taluk. The study area lends its name to various art forms and culture, such as Mysore Dasara, Mysore Painting; Mysore Pak (sweet dish), Mysore Masala Dosa; brands such as Mysore Sandal Soap, Mysore Ink; and styles and cosmetics such as Mysore Peta (a traditional silk turban) and Mysore Silk sarees. The taluk has four hoblis namely Kasaba, Ilavala, Varuna and Jayapura. The climate is semiarid tropical and the average annual rainfall of 798 mm with 55 rainy days (CGWB, 2012). The temperature ranges from 120 to 350 C.
Figure1: Location and Survey of India Topomap of Mysuru taluk
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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METHODOLOGY The methodology adopted consists of meaningful information extraction from Remote Sensing Satellite image, data preparation, interpretation (on-screen visual), Ground Truth Check (GTC), map finalization and database organization (NRSC, 2011). LU/LC maps are prepared using satellite image in conjunction with collateral data like SoI topomaps on 1:50,000 scale by considering permanent features such as major roads, drainages, power-lines, railways, settlements, co-ordinates and village boundaries (Manjunatha et al,
2015a). On‐screen Visual Image Interpretation Techniques (VIIT) are extracted manually and compared with digitally extracted vector layers in delineating land use land cover categories. Multi-temporal Resourcesat-1 of LISS III data of 2002 acquired during kharif (Aug –Nov), and rabi seasons (Jan- Mar) are acquired to estimate the spatial distribution variability of cropping pattern (NRSC, 2011). Preliminary interpreted LULC features from satellite images are updated by limited field visits & information and the final thematic details are transferred onto the base maps. Supervised classification Supervised classification analyses are carried out on multispectral IRS-1D, LISS-III FCC with medium scale through ArcGIS v10 (Figure 3). The LU/LC patterns are digitized based on the standard schemes developed by National Remote Sensing Agency (NRSA, 1995). Maximum Likelihood Classification (MLC) scheme is one of the most widely used image classification technique adopted on LISS-III images for mapping all the land use/cover classes. Before the selection of training samples, empirical analysis of satellite imagery and specific features on the toposheets are investigated carefully. For most of the classes, a minimum number of training samples were 100. Selecting training samples for water was tough because of the dense canopy of thick trees along with the river channel and lack of water in the river channels since the acquisition date of imagery was in mid-January and at that time most of the rivers carry less water as compared to the monsoon season. Changes in land surface conditions can affect the volume, timings and quality of run-off water. Different LU/LC are delineated and classified based on the key elements of image characteristics like tone, texture, shape, shadow, pattern, association, background etc (Table 2). Materials used i. Base map: Survey of India toposheets of 57D/7,
57D/8, 57D/11, 57D/12, 57D/15 and 57D/16 in 1:50,000 scale (Figure 1). Source: Survey of India (SoI) Office, Govt. of India, Bengaluru.
ii. Satellite Data: IRS-1D LISS-III of 23.5m Resolution and PAN of 5.8m (Nov-2001 & Jan-2002). Source:
National Remote Sensing Agency (NRSA), Hyderabad.
iii. GIS software’s: Erdas Imagine v2011 and Arc GIS v10.
iv. GPS: Garmin 12 is used to mark exact boundaries and to check the conditions of the land use/land cover patterns during field visits.
Figure 2: Flow chart of showing the methodology adopted in Land Use/Land Cover analysis
Figure3: IRS-1D, LISS-III (12th Jan 2002) Satellite Image of Mysuru taluk
Satellite data:
IRS-1D, Pan+LISS-III, 2 Seasons Geocoded data
Data Source
Collateral data:
i. SoI toposheets ii. Forest Map Base Map
Image Analysis
Classification System
Image Interpretation
Preliminary Interpreted Maps
Ground Truth Check
Post field correction/ Modification
Final Land Use/Land Cover Classification Maps
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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Table 1: Descriptions of Land Use and Land Cover Classification Scheme – NRSC (2011)
Table 2: Image Characteristics of various land use/land cover categories as seen in FCC (Dinakar, 2005)
Sl/N LU/LC Category
Tone/ Color Size Shape Texture Pattern
1. Barren rocky/ Sheet rock
Greenish blue to yellow to brownish
Varying in size
Irregular, discontinuous
Coarse to medium Linear to contiguous and dispersed
2. Built-up land Dark bluish green
Small to big Irregular Coarse Clustered to scattered
3. Crop land Bright red to red Varying in size
Regular to irregular
Medium to smooth Contiguous to non-contiguous
4. Deciduous forest
Red Varying in size
Irregular, discontinuous
Smooth to medium (depends on crown density)
Contiguous to non-contiguous
5. Fallow land Yellow to greenish blue
Varying in size
Irregular, discontinuous
Course to medium Contiguous to non- Contiguous
6. Forest plantation
Light red to red Varying in size
Regular to irregular
Smooth to medium Contiguous to non-contiguous
7. Kharif crops Bright red Varying in size
Regular to Irregular
Medium to Smooth Contiguous to non- Contiguous
8. Land with scrub
Light yellow to brown to greenish blue
Varying in size
Irregular, discontinuous
Coarse to mottled Contiguous dispersed
9. Mining/ Industrial area
Light bluish to black dark gray
Small to medium in size
Irregular in shape Mottled texture Contiguous dispersed
10. Salt affected land
White to light blue
Small to medium
Irregular, discontinuous
Smooth to mottled Dispersed, non-contiguous
11. Scrub Forest Light Red to dark brown
Varying in size
Irregular, discontinuous
Course to medium (depends on crown density)
Contiguous to non- Contiguous
12. Water bodies Light blue to dark blue (Subject to depth, weeds)
Small, medium, large
Regular to Irregular
Smooth to mottled Non-contiguous dispersed
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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RESULT ANALYSIS Level-I Classification Agricultural land The agricultural land use is a function of land productivity and land utilization practices over a period of time (NRSC, 2011). These covers farming, fallow, plantations, production of food, fiber and other commercial/ horticultural crops including land under crops (irrigated and un-irrigated) etc. This category covers an area of 600.81 km2 (74.57%) (Figure 5, Table 3). Built-up land It is an area of human habitation comprised of intensive use of land activities such as cities, towns, shopping centers, industrial & commercial complexes, institutions, villages, highways, transportation, power lines, communications and other facilities in association with water, vegetation and vacant lands (Anderson et al, 1976). Collectively any man-made constructions due to non-agricultural use are included under this category (Basavarajappa et al, 2013). The total aerial extent of built-up land is 126.01 km2 (15.64%) (Figure 5, Table 3). Forest Area within the notified forest boundary bearing an association predominantly of trees, other vegetation types, timber and other forest products (Manjunatha et al, 2018). The term forest is used to refer to land with a tree canopy cover of more than 10 percent and area of more than 0.5 ha. Forests are determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 mts (FAO, 2017). Satellite data has become useful tool in mapping the different forest types and density classes with reliable accuracy through visual as well as digital techniques (Madhavanunni, 1992; Roy et al, 1990; Sudhakar et al, 1992). The total forest cover measures an area of 19.86 km2 (2.46 %) (Figure 5, Table 3). Water bodies This category comprises areas with surface water in the form of ponds, lakes, tanks and reservoirs (NRSC, 2011). This class comprises areas of surface water, either impounded in the form of ponds, lakes and reservoirs or flowing as streams, rivers, canals, etc (Dinakar, 2005). These are clearly observed on standard FCC in different shades of blackish blue to light blue color depending on the depth of water bodies (Manjunatha and Basavarajappa, 2015b). The area occupied by this category is 36 km2 (4.46%) (Figure 5, Table 3).
Wastelands These are described as degraded land which can be brought under vegetative cover with reasonable effort and which is currently under utilized and land which is deteriorating for lack of appropriate water and soil management or on account of natural causes (NRSC, 2011). Wastelands can result from inherent/ imposed disabilities such as locations, environment, chemical and physical properties of the soil/ financial/ management constraints (NWDB, 1987). The total aerial extent of wasteland covers about 10.78 km2 (1.33%) (Figure 5, Table 3). Others This can be treated as miscellaneous due to their nature of occurrence, physical appearance and other characteristics (Basavarajappa et al, 2017) in the integrated thematic layer noticed in eastern and western parts covering an area of 9.88 km2 (1.22%) (Figure 5, Table 3).
Figure.4. Level-I LU/LC Classified map of Mysuru taluk Table 3: Level-I Land Use /Land Cover Classification of Mysuru taluk
S/N Land pattern Area (km2)
Percentage (%)
1. Agricultural land
600.8149 74.57
2. Built-up land 126.0137 15.64
3. Forest land 19.8649 2.46
4. Water bodies 36.0077 4.46
5. Wastelands 10.7862 1.33
6. Others 9.8859 1.22
Total 803.3733 99.68
Total Geographical Area
805.6362
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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Figure 5: Pie-chart depicting Percentage of Level-I LU/LC categories of Mysuru taluk Level-II Classification Agricultural plantations These are the areas under agricultural tree crops exhibit a dispersed or contiguous pattern planted adopting agricultural management techniques (NRSC, 2011). Use of multi-season data will enable their separation in a better way. It includes agricultural plantation (like tea, coffee, rubber etc.) horticultural plantation (like coconut, arecanut, citrus fruits, orchards, fruits, ornamental shrubs and trees, vegetable gardens etc) and agro-horticultural plantation (NRSC, 2011). Differentiation of plantation from cropland is possible by multi-temporal data of period matched harvesting time of inter-row crop/flowering of the plantation crops. Overall, Rabi season data is found to be better discrimination of plantations from croplands. The total area under this category is 53.98km2 (6.7%) (Figure 7, Table5). Barren rocky/Stony Waste As the area is exposed to the direct action of sun and wind, most of the area remains barren (Dinakar, 2005). These are the lands characterized by exposed massive rocks, sheet rocks, stony pavements or land with excessive surface, accumulation of stones that render them unsuitable for production of any green biomass. Such lands are easily discriminated from other categories of wastelands due to their characteristic spectral response (Basavarajappa et al., 2017). On FCC, they appears as greenish blue to yellow to brownish in tone with varying size associated with steep isolated hillocks, hill slopes and eroded plains. These are notified as linear forms within the plain land mainly due to varying lithology in northern and southern parts of the taluk (NRSC, 2011) covering an area of 1.17km2 (0.14%) (Figure 7, Table 5). Crop lands It includes kharif, rabi and zaid croplands along with area under double or triple cropping patterns (NRSC, 2011) including irrigated and un-irrigated, fallow, plantation etc (NRSA, 1989). The area under crops have digitized based on the standing crops as on the date of satellite image acquisition using both Kharif & Rabi seasons. Cropped
areas appear in bright red toned in color with varying shape and size in a contiguous to non-contiguous pattern. They are widely distributed in different terrains; prominently appear in the irrigated areas irrespective of the source of irrigation. This category covers an area of 539.81 km2 (67%) (Figure 7, Table 5). Degraded forest Forest cover with less than 10% is called as degraded forest. The degradation is brought about by maltreatment meted out by repeated felling, grazing and forest fires (Manjunatha et al, 2015a). On the contrary, if further ravaged it, ultimately degrades into thorny type and ultimately dry grass prevails and naked boulders are exposed. These are notified in the south-western corner of the taluk with an aerial extent of 5.05 km2 (0.62%) (Figure 7, Table5). Fallow land The lands which are taken up for cultivation but are temporarily allowed to rest, un-cropped for one or more season, but not less than one year (NRSC, 2011). These are particularly devoid of crops at the time; when the imagery is taken from both seasons. On FCC, fallow land shows yellow to greenish blue tone, irregular shape with varying size associated with amidst crop land as harvested agriculture field (Basavarajappa et al, 2017). The total area under this category is 7.00km2 (0.86%) notified around the city boundary limits (Figure 7, Table5). Forest plantations These are the areas of tree species of forestry importance, raised and managed especially in notified forest areas. The species mainly constitute teak, Sal, eucalyptus, casuarinas, bamboo etc (NRSC, 2011). These are artificially planted areas with tree cover, either in the open spaces or by clearing the existing forests for economically inferior species (Dinakar, 2005). New and young plantations can be readily separated from contiguous forested areas (Pushpavathi, 2010). The area occupied by this class is about 1.23km2 (0.15%) observed in south-western corner of the study area (Figure 7, Table 5). Lakes/ Tanks It is the natural course of water flowing openly on the land surface along a definite channel occupied either as seasonal or perennial river systems (Basavarajappa et al, 2017). Rivers and tanks are the major water sources in the taluk. 23 major and 62 minor lakes and tanks have been extracted effectively from LISS-III image based on the color/ tonal variation from dark to light blue (Satish et al, 2008). This covering an area of 10.12 km2 (1.25%) (Figure 7, Table 5).Mysore has the Biggest 'Walk-Through Aviary' called Karanji Lake in India.
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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Land with scrub Scrub lands are observed along the ridges, valley complex, linear ridges and steep slope areas. Most of these areas are characterized by the presence of thorny scrub, herb species, many hillocks of steep and domal shaped are associated with poor vegetal cover (Basavarajappa et al, 2014). This category covers an aerial extent of 9.4 km2 (1.16%) noticed majorly in southern, southern-western parts and in northern parts of the taluk (Figure 7, Table 5). Mining/ Industrial Wastelands Mining areas encompass area under surface mining operations. Industrial areas include a wide array of land uses from light manufacturing to heavy manufacturing Plants (Anderson et al, 1976). These are areas of stockpile of storage dump of industrial raw material or slag/effluents or waste material or quarried/ mixed debris from earth's surface (NRSC, 2011). This category covers an area of 1.00 km2 (0.12%) (Figure 7, Table 5). Magnesite mine is observed in Karya village in southern part of the taluk covering an area of 15.89 hectares including overburden and mine wastes. TVS is one of the major industrial lands noticed in Kadakola village with an aerial of 58.82 hectares. Moist & Dry Deciduous Forest Moist deciduous forests are more pronounced in the regions which record rainfall between 100-200 cms with main species of Teak, sal, sandalwood and other (NCERT, 2019). Dry deciduous forest covers vast areas of the country, where rainfall ranges between 70 -100 cms and interspersed with patches of grass. As the dry season begins, the trees shed their leaves completely and the forest appears like vast grassland with naked trees all around (NCERT, 2019). Multi-temporal data, particularly during October and March/April seasons help in their discrimination from other forest types. On FCC, it appears as dark red to red tone mainly due to rich in timber trees like Teakwood, Bamboo, Eucalyptus plantations etc. Chikkanahalli is one of the state reserved moist-dry deciduous forests identified in the southern-western part of the study area through LISS-III satellite image. This category covers an area of 5.83 km2 (0.72%) (Figure7, Table 5). Reservoir/ River A reservoir is an artificial lake created by construction of a dam across the river specifically for the generation of irrigation, water supply, hydro-electric power for domestic/ industrial uses and flood control (Dinakar, 2005). The introduction of a huge reservoir would be disturbing the delicate balance between soil, water and plants through rise in groundwater table (water-logging), (Piyoosh Rautela et al, 2002). River Cauvery is the primary sources
of irrigation, domestic and industrial purposes in the study area (CGWB, 2012). Krishna Raja Sagara (KRS) dam is built across River Cauvery in north-western part and the outlet water flow from western to eastern direction in northern boundary of the taluk. The reservoir along with its stream and canals stores an aerial extent of 25.88 km2 (3.20%) of water in the study area (Figure 7, Table 5). Artificial water course of canals are constructed for KRS water outlet in use of irrigation and to drain out excess water from agricultural lands (NRSC, 2011). Rural (Villages) These are the built-up areas, smaller in size, mainly associated with agriculture and allied sectors and non-commercial activities. They can be seen in clusters non- contiguous or scattered (NRSC, 2011). Land used for human settlement of size comparatively less than the urban settlement of which more than 80% of people are involved in agricultural activities (Pushpavathi, 2010). Villages can be clearly noticed from toposheet & satellite images with number of houses, inter spread with trees and agriculture fields especially in south western parts of study area occupied by deciduous forest of Chikkanahalli (Basavarajappa et al., 2017). The area occupied by this class is about 11.36 km2 (1.41%) (Figure 7, Table 5). Salt-affected land The land that has excess salt in the soils with patchy growth of grasses (NRSC, 2011). These are found in river plains and in association with irrigated lands and adversely effecting the growth of most of the plants due to the action or presence of excess soluble or high exchangeable sodium. The areas are delineated based on white to light blue tone and its situation (Dinakar, 2005). Salt affected lands are observed near Sindhuvalli village with an extent of 0.04 km2 (Figure 7, Table 5) noticed in southern part of the taluk. Scrub Forest Forest blanks which are the openings amidst forest areas, devoid of tree cover, observed as openings of assorted size and shapes as manifested on the imagery are also included in this category (NRSC, 2011). Scrub forest of Chamundi hill is noticed in central part of the taluk having canopy density less than 10% during extreme summer conditions (FAO, 2017). They appear as light red to dark brown tone on standard FCC due to canopy covers. This category covers an area of 7.73 km2 (0.96%) (Figure 7, Table 5). Chamundi hill is observed at the fringes of forest cover and settlements, where there is biotic and abiotic interferences occurs. Tree groves These are clump of trees that doesn't have much undergrowth and occupies a contained area such as a
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small orchard planted for the cultivation of fruits or nuts (Basavarajappa et al., 2019). A group of trees that grow close together are noticed extensively towards eastern and western parts of the study area, generally without many bushes or other plants underneath. This category covers an area of 9.88 km2 (1.22%) (Figure 7, Table 5. Urban (Towns and Cities) It includes residential areas, mixed built-up, recreational places, public/ semi-public utilities, communications, public utilizes/ facility, commercial areas, reclaimed areas, vegetated areas, transportation, industrial areas and their dumps, and ash/cooling ponds (NRSC, 2011). Land used for human settlement of population more than 5000 of
which more than 80% of the work forces are involved in non-agricultural activities is termed as urban land use (Pushpavathi, 2010). Most of the land covered by building structures is parks, institutions, playgrounds and other open space within built up areas. Urban land occupies an area of 113.80 km2 (14.12%) (Figure 7, Table 5). This class usually occurs in combination with, vegetated areas that are connected to buildings that show a regular pattern, such as vegetated areas, gardens, industrial and/or other areas (FAO, 2017). Mysuru is the second largest city after Bengaluru in Karnataka State having the population of 8,87,446 as per 2011 provisional census figures and it increased from 7,85,800 in 2001 (Shankar and Vidhya, 2013).
Figure 6: Level-II LU/LC Classified map of Mysuru taluk Table.4. General Conditions of LU/LC patterns during Ground Truth Check (GTC)
S/N Location Name Latitude Longitude Field Conditions
9. Karya village 12° 9'58.12" 76°38'39.36" Abandoned Magnesite mine observed with 75hectares
10. Bettadabeedu village 12°11'13.20" 76°29'54.07" Moist & dry deciduous forest covers 3.08 km2 area here
11. Krishna Raja Sagara 12°25'35.15" 76°30'56.08" Back water of KRS dam built across river Cauvery in NW parts
12. Chikkanahalli 12°11'1.29" 76°31'39.50" Scattered cluster of human settlement associated with more than 80% of agricultural activities
13. Sindhuvalli village 12°11'24.63" 76°37'23.14" Excess salt in the soil with patchy grasses observed
14. Chamundi hill 12°16'22.81" 76°40'10.68" Chamundi forest covered with lush green vegetation
15. K.R. Circle-City Centre 12°18'31.53" 76°39'11.03" Mysore is the third most populated city in Karnataka
16. Hosur village 12°13'35.14" 76°30'13.40" Rural organic farms had noticed
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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Table 5: Level-II Land Use/Land Cover Classification of Mysuru taluk
S/N Land pattern Area (km2)
Percentage (%)
1. Agricultural Plantation 53.9898 6.70
2. Barren rocky/ Stony waste 1.1750 0.14
3. Crop land 539.8172 67.00
4. Degraded Forest 5.0567 0.62
5. Fallow land 7.0078 0.86
6. Forest plantations 1.2368 0.15
7. Lakes/ Tanks 10.1235 1.25
8. Land with scrub 9.4097 1.16
9. Mining/ Industrial wasteland
1.0067 0.12
10. Moist & Dry Deciduous Forest
5.8340 0.72
11. Reservoir/ River/ Stream 25.8840 3.20
12. Rural 11.3618 1.41
13. Salt Affected land 0.0424 0.00
14. Scrub Forest 7.7373 0.96
15. Tree Groves 9.8859 1.22
16. Urban 113.8040 14.12
Total 803.3726 99.62
Total Geographical Area 805.6362
Figure 7: Pie-chart depicting Level-II LU/LC categories of Mysuru taluk
Figure 8: Betel leaf garden near Agrahara
Figure 9: Google Earth image of Barren/ sheet rocky near visveshwara nagara
Figure10: Crop land near Dadadakalla halli village
Figure11: Fallow land near Hootagalli
Figure 12: Coconut plantation near Chikkanahalli
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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Figure 13: Karanji lake
Figure 14: Abandoned Magnesite Mine near Karya village
Figure 15: Back water of Krishna Raja Sagara
Figure 16: Bird view of Chamundi hill
Figure 17: Bird view of built-up area from Chamundi hill
Level-III Classification Double Cropped (Kharif + Rabi) The main cropping season, kharif, starts from May and ends by September. The cropping intensity is very high due to physical factors such as flat terrain, fertile soil and irrigated from canal system. Most of the double crop areas are concentrated adjacent to the rivers flowing in the study area (Pushpavathi, 2010). On FCC, the double crop show a dark red tone with square pattern representing soil covers with higher amount of moisture near the streams (Basavarajappa et al, 2017). The cultivated lands at elevated zones represent bright red tone representing less amount of moisture and deeper levels of groundwater prospect zones. This category has been identified and mapped using the two season satellite images which covers an area of 63.90km2 (7.93%) (Figure 19, Table6). Kharif These are the standing crops from June to September associated with rainfed crops under dry land farming and limited irrigation. Kharif crops are depicted by red tone on standard FCC image. The major kharif crops grown area maize, jowar, bajra, cotton, sugarcane, pulses grown under rainfed condition, whereas paddy are grown under irrigated conditions (CGWB, 2012). The land occupies an area of 475.9km2 (59.07%) (Figure 19, Table 6). Table 6: Level-III Land Use/Land Cover Classification of Mysuru taluk
S/N Land pattern Area (km2) Percentage (%)
1. Double (Kharif + Rabi) crops
63.9086 7.9326
2. Kharif crops 475.9086 59.0723
Total 539.8172 67.0049
Total Geographical Area 805.6362
Figure 18: Level-III LU/LC Classified map of Mysuru taluk
Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India
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Figure 19: Pie-chart depicting Level-III LU/LC map of Mysuru taluk DISCUSSION Scientific assessment of our land resources is a prerequisite for optimal planning of natural resources of the country (NRSC, 2011). Remotely sensed data has made it possible to study changes in land cover and its monitoring in less time, at low cost and better accuracy (Anji Reddy, 2001; Kachhwaha, 1985). The present study reveals that 5 major classes in Level-I (Figure 4; Table 3) 16 classes in Level-II (Figure 6; Table 4) and 2 classes in Level-III have been effectively generated by IRS-1D, PAN+LISS-III satellite images (Figure 8; Table 5). Kharif crops are dependent mainly of rainfall and occupy the maximum areal extent of 475.9 km2 (59.07%) that indirectly reflect that groundwater dependent crops are less. Double crops are noticed adjacent to the perennial rivers Cauvery and in its drainage patterns which provide well developed canal system for irrigation purpose (Basavarajappa et al, 2014). The major crops grown are cotton, ragi, vegetables and mango practiced in large agricultural fields (CGWB, 2012). LU/LC provides necessary tasks to enhance human occupation to the changing social, economic and natural environmental conditions. The area occupied by built-up land is 126.01 km2 (15.64%) and further increase in population can negatively impacts on biodiversity and also disturbs natural land cover, increase in soil erosion into streams and lakes (Manjunatha et al, 2015a). The purpose of land-use planning is to support decision makers in selecting the best practice for specific lands that meet the needs of people while safeguarding natural resources & ecosystem services for current and future generations (FAO, 2017). CONCLUSION The study highlights the capability of Geospatial technology in extracting meaningful and valuable information which is extremely important in monitoring and management of dynamic LULC features. Precise and timely interpretation of LULC classification data will be an effective tool in addressing the spatial changes, environmental & socio-economic concerns, growing demand for economic natural resources, risks related to public health, cropping patterns, vulnerability to certain
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Accepted 26 June 2020 Citation: Manjunatha MC, Basavarajappa HT (2020). Assessment of Land Use Land Cover Classification through Geospatial Approach: A Case Study of Mysuru Taluk of Karnataka State, India. Journal of Environment and Waste Management, 7(1): 326-338.
