Investigating the effect of the landslide deposition area for susceptibility assessment in Brazil

Shallow landslides are a frequent type of mass movement in mountains regions. The recognition and mapping of shallow landslides are very important to better understand the characteristics of the hazard (e.g., triggering factors, conditional factors) and the magnitude of the event, as well as to facilitate susceptibility, vulnerability, and risk analysis. In Brazil, they are one of the most frequent and destructive natural hazards; each year numerous shallow landslides are triggered by rainfall, particularly in the south and southeastern regions of the country, resulting in social and economic impact. The construction of landslide inventories in Brazil is still incipient since not all mass movement events that occurred are documented and no mapping guidelines exist. Thus, this research aims to investigate how the inclusion/exclusion of the deposition area in a shallow landslide inventory mapping influences the results of a susceptibility assessment. The study area is the Gurutuba watershed, located in the municipality of Itaóca, São Paulo state, southeastern Brazil. Two shallow landslide inventories of the 2014 high magnitude mass movement event were created based on Google Earth Pro images dated 2014/10/08. The criteria applied for visual mapping were the absence of vegetation, shape, size, drainage network distance, planar rupture surface, altimetric variation, and slope position. The inventories were constructed based on the same visual guidelines, the difference between them is regarding the deposition area. Inventory 1 (INV1) includes rupture, transport, and deposition area, while inventory 2 (INV2) only includes rupture and transport area but excludes the deposition area. A bivariate statistical approach, i.e., the informative value method, was applied to create a susceptibility map and compare the performance of INV1 and INV2. Besides the inventories, four morphological thematic variables (aspect, slope, elevation, and curvature) derived from a digital elevation model (DEM) from the SRTM mission, re-sampled to 12.5 m, were used for this analysis. The thematic variables slope, aspect, and elevation did not generate a substantial difference with the inclusion/exclusion of the deposition area and showed similar statistical results for both inventories. The morphological classes with high susceptibility were slope between 40°and 50°, E and SE orientation, and elevation between 400 and 500 m. Curvature presented different results for each inventory, while in INV1 convex areas were the most susceptible, with INV2 both convex and concave areas were considered susceptible. The validation indicated slightly better performance of INV2 for the susceptibility mapping based on the success rate (AUC 0.775) and prediction rate (AUC 0.758) than INV1, which resulted in a lower success rate (AUC 0.758) and prediction rate (AUC 0.740). These results indicate that considering the deposition area for shallow landslide recognition and mapping affects the assessment of susceptibility mapping in a tropical environment. The criteria applied for shallow landslide mapping are not always mentioned in Brazilian studies despite the landslide inventory being the most important input variable for susceptibility assessment. Further analysis should be carried out in other regions of the country, as well as with more accurate resolution data if available.