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Ecosystems in urban areas are strongly influenced by anthropogenic activities. Spatial-temporal transformations that occur in different classes of land use/cover like Built-up, Vegetation and Water are the key drivers of global change that reflects the territorial and socio-economic progress of an area and have significant implications for many policy issues. The current study uses a maximum likelihood classification method to map five different land use land cover classes in the openly available Landsat satellite images of 2008 and 2016 for selected urban boundaries of Srinagar, India. Pixel to pixel change detection strategy is implemented to find out the changes occurred in individual land use land cover class. The results are compared and illustrated in the form of graph and maps for providing an interactive visual representation for administrators and policymakers.

Land Use Land Cover Change Detection using Remote Sensing and GIS in Srinagar, India