Land Use Land Cover Change Detection Using Hybrid Machine Learning Algorithms – Anaimalai Hills, Tamil Nadu, India

Effective land management and environmental monitoring rest on the ability to analyze the Land Use Land Cover (LULC) changes on the earth's surface. Geographic Information Systems (GIS) and remote sensing techniques are used in this work to methodically measure the LULC changes. This work focused on finding the LULC changes that happened in the region of Anaimalai Hills, Tamil Nadu, India for the years 2019, and 2021. We examined LULC changes using Landsat-8 satellite images. The classification process employs a hybrid approach with supervised, and unsupervised machine learning classifiers, producing a detailed LULC map that outlines water, and vegetation in the study region. The overall accuracy obtained was 95.704 % for 2019 and 96.484 % for 2021. The LULC results assist land resource management (LRM) safeguard the environment from a huge loss, specifically in vegetation and water bodies.