Integrating the NDVI-Random Forest Classification for Vegetation Analysis - Yercaud Hills, India

The Normalized Difference Vegetation Index is a key study for monitoring environmental changes precisely in forest-covered regions. In the domain of Geographic Information Systems and Remote Sensing, the Yercaud Hills in India experience substantial variations in land cover, mostly through deforestation, impacting the area’s vegetation. Using multispectral data from Landsat $9 / 8$ satellites, this study employs the Normalized Difference Vegetation Index as training input for a random forest classifier to produce land cover maps for the years 2023 and 2024. With a good average accuracy rate of $94.62 \%$ in land cover mapping, this work aims to provide valuable insights for forest resource planners to address considerable forest loss. Through precise assessments of land cover dynamics, this work serves as a critical resource for informed decision-making, aiding in promoting sustainable forest management and conservation efforts in the Yercaud Hills region.