An experimental geospatial intelligence platform developed for dynamic landslide risk monitoring and near real time early warning in the Chittagong Hill Tracts (CHT) of Bangladesh.
Run Landslide Risk AnalysisA landslide is the downward movement of rock, soil, or debris under the influence of gravity, which can occur slowly over time or rapidly as a sudden and potentially catastrophic event. They are among the world's deadliest geohazards.
Bangladesh and surrounding regions face heightened risk due to steep hill terrain, intense monsoon rainfall, deforestation, and rapid urbanization in vulnerable zones.
Landslides are one of the most localized and rapidly evolving natural hazards in the Chittagong Hill Tracts (CHT) of Bangladesh, often triggered by intense rainfall, unstable slopes, and environmental degradation. This project presents an experimental geospatial intelligence platform designed for dynamic landslide risk prediction and near real time early warning.
The system integrates terrain conditions, vegetation characteristics, and rainfall information to generate automated district level landslide risk assessments and operational warning outlooks. Through an interactive Google Earth Engine dashboard, users can analyze historical landslide conditions as well as short range forecast outlooks for landslide prone regions. The platform is designed to support localized hazard monitoring, anticipatory action, and rapid risk interpretation through a scalable and automated geospatial workflow tailored for the complex hill environments of Bangladesh.
Our models are trained on historical landslide data, satellite imagery, elevation, slope, soil type, and land-use patterns to generate accurate risk predictions.
Powered by Google's planetary-scale geospatial analysis platform, our tool processes terabytes of satellite data in real time to map vulnerable zones.
We deliver timely alerts via loudspeaker announcements, SMS notifications, and emergency service coordination to protect at-risk communities.
Interact with the live geospatial map — explore risk zones, run analysis, and view alert layers across the region.
Team Risk Detectives is a student led research collective dedicated to bridging the gap between complex atmospheric science and community resilience. The initiative "Near Real-time Landslide Risk Prediction & Early Warning System" is spearheaded by Faozia Anzum Itu (Team Lead, MS Student), Md Saiful Islam (MS Student), and Pritom Bose Aapon (Undergraduate Student, 4th Year), a trio of researchers affiliated with the Department of Meteorology at the University of Dhaka. Operating at the high stakes intersection of geospatial analytics, environmental monitoring, and disaster risk science, the team works collaboratively to transform raw Earth observation data into localized, life saving intelligence.
Our vision is to redefine how Bangladesh prepares for geological hazards by transforming vast streams of Earth observation data into precise, localized, and life saving intelligence. We believe that by decoding environmental signals today, we can safeguard the vulnerable communities of tomorrow.
We gratefully acknowledge the department for its continuous technical guidance and research mentorship. This collaboration has been fundamental in evolving this research from a conceptual framework into a functional system for the benefit of the nation.
Team Lead · Masters Student
Department of Meteorology
University of Dhaka
Undergraduate Student (4th Year)
Department of Meteorology
University of Dhaka
Masters Student
Department of Meteorology
University of Dhaka