| In the present study, Land use and Land cover (LU/LC) categories has been classified in the form of thematic maps to analysis change detection in the Kaliasot watershed area, belongs to Bhopal and Raisen district of Madhya Pradesh. Based on Remote Sensing (RS) and Geographic Information System (GIS) techniques, the study is an attempt to identify various Land use and Land cover classes and monitor the changes in land use / land cover patterns from 2009 to 2018 within the Kaliasot watershed area. To prepare land use / land cover maps, the satellite data of IRS 1D LISS-III of years 2009 and 2018 has been used for interpretation through ArcGIS and Erdas Imagine software. Using Maximum Likelihood classifier Supervise Classification technique is applied to prepare land use / land cover maps of the study area. The accuracy of the mapping is verified using Google Earth satellite data through linkages in Erdas Imagine and selected field observations. During the study it is observed that six land use / land cover classes i.e. agriculture, built-up area, waterbodies, river, industrial area, and land with/without scrub area has been identified. As the Bhopal is capital of Madhya Pradesh, it is observed that encroachment along the riverbank and haphazard urbanisation has been increased rapidly during last two decades. In the study area, major changes in land use / land cover classes are observed as conversion of major agriculture area into built-up area between the year 2009 and 2018. The mapping results indicate that built-up area and industrial area has been increased 35.86% (68.93 km2) and 0.12% (0.25km2) respectively. However, agriculture land and land with/without scrub have decreased by -35.96% (-69.01 km2) and -0.41% (-0.79 km2) respectively. The analysis and findings of the study highlights appropriate planning and policy implications for the sustainable land use / land cover management in the Kaliasot watershed using geospatial technology.
Keywords: Land use change; RemoteSensing; GIS,Spatial data, Google Earth
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