Machine Learning based Monsoon Forecasting and Drought Risk Assessment system using Indian climate data, Random Forest classification, state-wise rainfall analytics, and interactive Streamlit visualization.
Predicting weekly drought score values using LSTM for time series analysis of daily soil & weather data.
DROPLETS is a project developed as part of the AI Project course (AI Project__3IA3) at ESPRIT, under the course code ESE.INFIA0010__3IA3. This project demonstrates the application of artificial intelligence techniques in a real-world context, designed by 3IA students.
GeoAI framework for spatiotemporal drought modelling in the Al-Kharj–Riyadh Basin, Saudi Arabia. Fuses CHIRPS, ERA5-Land, MODIS, and GLDAS/FLDAS data (2000–2024) into gridded SPEI-3 indices, comparing an interpretable XGBoost baseline with a ConvLSTM deep-learning model for arid-region drought early-warning.
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