Geospatial Analysis of Land Use and Land Cover Dynamics Using Landsat Data: A Case Study of Ferozpore Nallah Watershed in Kashmir Valley

Findings of LULC change detection are important for understanding the influence and impacts of natural and anthropogenic activities on the watershed resource management. The present study utilizes the Remote Sensing (RS) & Geographic Information System (GIS) technology to categorize and identify changes in the Ferozpore nallah watershed in district Baramulla of Kashmir valley in India from 2001 to 2021. Supervised classification with maximum likelihood approach was employed to classify and generate the LULC maps. High-resolution Google Earth Pro historical images were used to evaluate the accuracy of the classified maps and were validated using overall accuracy and Kappa statistics. Nine LULC classes (agriculture, horticulture, forest, built-up, barren land, marshes, waterbodies, pastures and scrubs) were mapped from the Landsat imagery obtained for the period 2001 and 2021. The findings of change detection analysis shows that the area under agriculture, forest and marshes decreased by 18.77%, 1.79% and 5.48%, respectively from 2001 to 2021. Whereas, area under horticulture, built-up, barren land, waterbodies, pastures and scrubs increased by 19%, 4.22%, 1.24%, 0.60%, 0.31% and 0.67%, respectively at the same time. The overall accuracy of the classified maps was 88.89% for 2001 and 94.44% for 2021 while the kappa co-efficient was 0.87 and 0.94 for 2001 and 2021, respectively. The results of this study provide data to the planners and policy makers in understanding the Land Use and Land cover scenario and insights towards formulating policies for an effective and eco-friendly natural resource management and sustainable land use in the watershed region.