Spatial datasets for benchmarking machine learning-based landslide susceptibility models

Landslide polygons were delineated through manual interpretation of high-resolution satellite imagery. The landslide-controlling factor data were extracted from topographic maps and Indonesia’s national digital elevation model (DEMNAS).

The landslide-event dataset was mapped by comparing pre- and post-event (Tropical cyclone (TC) Cempaka, which occurred on 27–29 November 2017) high-resolution satellite imageries and conducting field surveys. The landslide polygons indicate areas with confirmed landslide occurrences, while the landslide-controlling factors data includes slope aspect, distance to river, distance to road, elevation, lithology, landuse, plan curvature, profile curvature, slope, stream power index, and terrain wetness index.