Assam_Geospatial_dataset

Floods are among the most devastating natural disasters, often resulting in significant loss of life and extensive damage to property and resources. Effective flood prediction and early warning systems are therefore essential for disaster mitigation and response.This study presents an AI-based Flood Prediction and Alert System that leverages spatial, hydrological, and temporal data to assess and forecast flood risks. The proposed framework consists of five integrated modules: flood classification using satellite imagery, water depth estimation through Digital Elevation Models (DEM), identification of flood-causing factors using climate data, temporal modeling for predicting flood timing, and automated alert generation for disaster management authorities.By employing deep learning models such as LSTM and hybrid ConvLSTM architectures, the system captures both short-term and long-term dependencies in data to generate accurate flood forecasts. Overall, the framework provides a scalable, data-driven approach to strengthening flood resilience and improving disaster preparedness.