LHASA uses a machine learning model that combines data on ground slope, soil moisture, snow, geological conditions, distance to faults, and the latest near real-time precipitation data from NASA’s IMERG product (part of the Global Precipitation Measurement mission). The model has been trained on a database of historical landslides and the conditions surrounding them, allowing it to recognize patterns that indicate a landslide is likely.