Exploring Change Detection in Classified Land Cover and Land Use Imagery: A Comprehensive Analysis

This research investigates the relationship between Land Use and Land Cover (LULC) in the Chambal and Yamuna Rivers region, using Bhuvan dataset’s LISS-III imagery. By employing Quantum Geographic Information System (QGIS) software, exploratory analysis was conducted and the Maximum Likelihood Classifier was utlized to extract features from satellite images. The method ensured accuracy through tailored statistical principles, yielding an impressive overall accuracy of 96.88%. The findings reveal intricate connections between LULC, exposing significant human impacts on the local ecology and hydrology. This study underscores the importance of resource management and environmental monitoring in dynamically changing landscapes. It emphasizes the crucial roles of QGIS and the Maximum Likelihood Classifier in extracting valuable insights from satellite data. By highlighting these complexities, the research contributes to understanding and addressing the challenges of sustainable land use and environmental conservation in rapidly evolving regions.