Carbon Lens-Senegal: A Multi-Source Machine Learning Approach for Forest Biomass Estimation in Tropical West Africa

A Novel Hybrid Machine Learning Approach and Basin Modeling for Thermal Maturity Estimation of Source Rocks in Mandawa Basin, East Africa

Systematic review papers of Machine Learning approaches for Soil Organic Carbon estimation in Africa

This review systematically examines the application of machine learning (ML) techniques in

Forest canopy height, biomass, and carbon stock datasets for the West Usambara Mountains, Tanzania

This repository contains forest canopy height (FCH), above-ground biomass (AGB), and a

A Preliminary Random Forest Baseline for Above-Ground Carbon Stock Estimation in Abuja Municipal Area Council Using Free Multi-Sensor Satellite Data: A GeoAI Approach

Accurate quantification of above-ground carbon (AGC) stock is essential for climate mitigation plann

AI- Driven Prediction of Lassa Fever Using Evolutional and Random Forest: A Machine Learning Approach for Enhanced Surveillance in West Africa

Lassa fever, a viral hemorrhagic fever endemic to West Africa, poses significant public health chall

Field data for validating the spatially continuous aboveground biomass estimation of forest-savannah mosaics in West Africa by combining GEDI LiDAR data and multi-sensor satellite observations

The AGB_validation_ICESat2_plot_data and AGB_validation_IFN2_plot_data files contain field data coll