Shallow landslide prediction and analysis with risk assessment using a spatial model in the coastal region in the state of São Paulo, Brazil

Abstract

Abstract. In Brazil, most of the disasters involving landslide occur in coastal regions, with population density concentrated on steep slopes. Thus, different approaches have been used to evaluate the landslide risk, although the greatest difficulty is related to the scarcity of spatial data with good quality. In this context, four cities located on the southeast coast of Brazil – Santos, Cubatão, Caraguatatuba and Ubatuba – in a region with the rough reliefs of the Serra do Mar and with a history of natural disasters were evaluated. Spatial prediction by fuzzy gamma technique was used for the landslide susceptibility mapping, considering environmental variables from data and software in the public domain. To validate the susceptibility mapping results, it was overlapped with risk sectors provided by the Geological Survey of Brazil (CPRM). A positive correlation was observed between the classes most susceptible and the location of these sectors. The results were also analyzed from the categorization of risk levels provided by CPRM. To compare the approach with other studies using landslide-scar maps, correlated indexes were evaluated, which also showed satisfactory results, thus indicating that the methodology presented is appropriate for risk assessment in urban areas and can be replicated to municipalities that do not have risk areas mapped.

Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling

“…Other predisposing factors include soil thickness and strength, rainfall direction, lithology, fracture, and root strength. The preparations of thematic data layers were essential for a landslide susceptibility mapping (enhancing or mitigating) [41]. Although the above factors were important controls, in practice, spatial distribution of those factors was difficult to determine.…”