Landslide susceptibility analysis is a common approach for assessing the risk of slope failures in areas affected by rainfall. During the rainy season, the city of Salvador, Brazil, often experiences slope failures and landslides. This research applied the infinite slope model using GIS as a screening method to assess landslide susceptibility in Salvador. The GIS-based model calculated the slope stability factor of safety by integrating spatial data, including soil parameters, slope angles, and depths of water penetration, to identify areas prone to landslide during rainfall events. Soil parameters were obtained from laboratory analyses of 392 samples collected from various locations in Salvador, which is considered an administrative subdivision organized by districts. Four water penetration depths (h = 1, 2, 3, and 4 metres) in the soil were simulated, and their influence on the slope factor of safety was analyzed. Susceptible areas for landslide were obtained by calculating the thickness of the unstable material or the weight of the surface layer as a function of water penetration depth. For h = 1 m, the total landslide-susceptible area was 1.24 km2, while for h = 4 m, the area increased to 42.75 km2. The 4-Liberdade/São Caetano district showed the largest area susceptible to landslides. The results from the GIS model were consistent with the historical landslide data and landslide susceptibility maps from Serviço Geológico do Brasil (CPRM – Brazil Geological Service) official dataset. The integration of the infinite slope model into GIS provided a valuable tool for improving landslide hazard management by screening landslide-susceptible areas at both regional and local scales.
Silva et al. (2026) studied this question.