Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil

Abstract

Weather-related disasters have caused widespread deaths and economic losses in developing countries, including Brazil. Frequent floods and landslides in Brazil are mostly climatic driven, often aggravated by human activities and poor environmental planning. In this paper, we aimed to map and discuss the susceptibility to landslides in the urban area of Ouro Preto, Brazil, a municipality with colonial and world heritage houses. We used data on precipitation, soil types, geology, digital elevation model (DEM), and land use and land cover (LULC) of high spatial resolution (1 m). The location of landslides in the urban perimeter was provided by the Civil Defense of Ouro Preto, and these were validated by fieldwork. A novel mathematical model based on multi-criteria decision-making (MCDA) and the Analytic Hierarchy Process (AHP) was used to map the susceptible areas to landslides. Results show that areas most affected by strong landslides were low-density vegetation (high susceptibility) and rocky outcrops (very high susceptibility). The largest areas susceptible to landslides are urban land use areas. Particularly, landslides that occurred in February 2022 in the region were related to intense soil saturation. With an average monthly rainfall of 122.60 mm, the uneven relief and edaphoclimatic characteristics had caused percolation of the surface runoff, naturally triggering landslides. This study supports mitigation efforts by local governments and decision-makers.