Leveraging Landsat Imagery and Support Vector Machine for Land Use/Land Cover Change Detection: A Case Study of the Panam River Watershed

¹ Sankalchand Patel College of Engineering, Sankalchand Patel University, Visnagar, Gujarat, India
² College of Food Processing Technology and Bio Energy, Anand Agricultural University, Anand, Gujarat, India
³ Swami Sachchidanand Polytechnic College, Sankalchand Patel University, Visnagar, Gujarat, India

^* Corresponding author: akilpochi@gmail.com

Abstract

This study investigates land cover/land use (LULC) changes within the Panam River Watershed between 2011 and 2023. Leveraging freely available Landsat imagery and geospatial technologies like remote sensing and GIS, the research analyzes four LULC classes: settlement, waterbodies, agricultural land, and wasteland. A supervised classification approach using Support Vector Machines (SVM) within ArcGIS software is employed to detect land cover for both years. The analysis reveals significant changes over the twelve-year period. Settlements and wastelands experienced increases of 2.3% and 9%, respectively. Conversely, waterbodies and agricultural land exhibited declines of 1.95% and 9.38%, respectively. The observed increase in settlements and wastelands, coupled with the decrease in waterbodies and agricultural land, raises concerns about potential environmental within the Panam River Watershed and raise important considerations for sustainable land management practices.