Exploring geospatial techniques for spatiotemporal change detection in land cover dynamics along Soan River, Pakistan.

Classification of land cover dynamics via satellite imagery has played indispensible services in developing effective management strategies for evaluation and management of water resources. The present study employed geospatial techniques, i.e., integrated GIS and remote sensing for effectual land change study. Hybrid classification approach was applied using ERDAS Imagine 11 to detect changes in land cover dynamics using satellite imagery of Landsat 4, 5 TM, Landsat 7 ETM, and Landsat 8 OLI for the years of 1992, 2002, and 2015, respectively. The study area was classified into four categories, i.e., vegetation, water body, barren, and urban area. Resultant maps, overlay maps, and post classification comparison maps were produced using ArcGIS 10.2 indicated remarkable shrinkage of water body up to 58.81%, reduction in vegetation area 53.24%, and increase in urban and barren area to 49.04 and 137.32%, respectively. The significant changes in land cover dynamics of Soan River are posing threats to its survival. Therefore, proper management, policies, and development of land use inventory are needs of the hour for saving Soan River.