Spatio-temporal Analysis of Land Use and Land Cover Dynamics using Multi-temporal Landsat Imagery in the Dantiwada Watershed, Gujarat, India

Abstract

Land use and land cover (LULC) change is an important indicator of landscape transformation and provides useful information for watershed planning and natural resource management. This study assessed spatio-temporal changes in LULC in the Dantiwada watershed, Gujarat, India, using multi-temporal Landsat satellite imagery for 2002, 2013, and 2024. Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI datasets were processed and classified using the Iterative Self-Organising Data Analysis Technique (ISODATA), an unsupervised classification approach. Five major LULC classes were identified: waterbody, barren land, built-up area, dense vegetation, and vegetation. Post-classification comparison was used to quantify the area and percentage distribution of each class across the 22-year study period. The results showed a marked reduction in barren land from 73.70% in 2002 to 58.22% in 2013 and 45.76% in 2024. Vegetation increased from 18.50% to 28.65% and 33.13%, while dense vegetation increased from 5.70% to 10.07% and 15.97% during the same period. The combined vegetation and dense vegetation classes increased from 24.20% in 2002 to 49.10% in 2024. Built-up area increased from 1.10% to 3.45%, and waterbody area increased from 1.00% to 1.69%. The findings indicate a substantial shift from barren land towards vegetated land cover within the Dantiwada watershed and provide baseline information for watershed-level land resource planning and long-term monitoring.