Geo Sentrix AI: AI-Based Disaster Risk Mapping Using Satellite Data

Landslides are among the most hazardous natural calamities that result in substantial damage to infrastructure, environment, and human lives, particularly in geographically vulnerable zones. Landslide prediction is an important task that has been hampered by the intricacy of terrain conditions and the inability of conventional mapping techniques. The present study proposes an advanced geospatial technology solution called GeoSentrix AI: Landslide Susceptibility Prediction System (India), which employs machine learning algorithms along with remote sensing technology for landslide susceptibility prediction. The proposed solution is based on the concept of using the Google Earth Engine (GEE) for large-scale computation of high-dimensional geospatial data. Moreover, the solution employs a Random Forest algorithm for analyzing terrain-related factors such as slope, aspect, curvature, NDVI, and hydrological factors for landslide susceptibility prediction. The proposed solution generates pixel-wise maps that help identify landslide hazard zones with greater accuracy.