Unveiling the Hydrological NDWI: Random Forest Analysis of Landsat Images - Siruvani Dam, India

As we travel across Earth’s varied topographies, changes in land cover display how nature and human activities interact and change over time. The main objective is to analyze water body changes around Siruvani Dam, India, between 2022 and 2024 using Landsat imagery and a random forest classifier trained with the hydrological Normalized Difference Water Index (NDWI) data. The results derived from the NDWI-based random forest machine learning model achieved an average accuracy of $97.045 \%$ for the classified maps. The findings from both 2022 and 2024 land cover maps hold significant implications for safeguarding water resources, assisting in sustainable management and decision-making for Siruvani Dam and other regions around the world.