Integrating SAR remote sensing and machine learning for comprehensive flood risk assessment in Kogi state, Nigeria

A GeoAI framework for coastal flood risk assessment: integrating remote sensing and socioeconomic data

Bangladesh’s coastal zone is widely recognized as one of the most hazard-prone regions of the world.

Integrating remote sensing and social sensing for flood mapping

Flood events cause substantial damage to infrastructure and disrupt livelihoods. Timely

Flood Risk Prediction Using Remote Sensing and Machine Learning — Tana River, Kenya

This project implements an end-to-end flood prediction pipeline for Tana River County, Keny

GIS and remote sensing-based hybrid AHP–machine learning framework for flood susceptibility and risk assessment in the Wolaita Zone, Southern Ethiopia

Evaluating Flood Vulnerability in the Loukous Basin, Northern Morocco: Integrating Machine Learning, Remote Sensing, and Climate Change Impacts

This study investigates flood-prone areas in the Loukous Basin, Northern Morocco, utilizing machine

MatteoSelden/Risk-assessing-desertification-through-remote-sensing-and-machine-learning

This project aims to provide a low-level tool to assess the risk of desertification over time. It fo