Executive Summary : | Land subsidence from coal mining activities in East India presents significant environmental, social, and economic challenges. To mitigate these impacts, a comprehensive understanding of its dynamics is essential. Technological advancements have shifted spatial data generation to satellite remote sensing, optical and microwave remote sensing data, Unmanned Aerial Vehicles (UAVs), Differential Interferometric synthetic Aperture Radar (DinsAR) techniques, and high-resolution ground penetrating radar (GPR) data. Traditional classification methods struggle to process large datasets. This study aims to combine geospatial, machine learning, deep learning, and GPR methods in a single platform for land subsidence study. The project aims to employ a multi-modal approach, integrating UAV, DInsAR, AI, and GPR, to assess and analyze land subsidence in coal mining regions of East India. The research will help policymakers in sustainable development, environmental planning, and management, and can be applied to other regions facing land subsidence. |