Geological Risk Estimation in Urban Hillslopes: Building Cadastral Mapping Using UAVs and Landslide Susceptibility Modeling with TRIGRS

The Metropolitan Region of Recife (RM-Recife) is one of Brazil's most affected areas by landslides, with the municipalities in the region frequently ranking among the most impacted by fatalities caused by these events. In light of this, it is essential to use methodologies that determine susceptibility and risk, particularly in urban areas undergoing constant changes due to inadequate human activities. The study covers a sub-basin with an occupied slope, covering an area of 104,824.81 m²and containing 513 buildings in the Dois Unidos neighborhood, North Zone of Recife, Pernambuco. The region faces challenges such as irregular settlements and territorial fragmentation, which increase its vulnerability to natural disasters. The study aims to estimate geological risk in two stages. The first involves using Unmanned Aerial Vehicles (UAVs) to map buildings on urban slopes susceptible to landslides. Digital Terrain Models (DTM), Digital Surface Models (DSM), Digital Elevation Models (DEM), and orthophotos were generated to conduct the cadastral survey. IBGE data were used to assess the population exposed to risk. Subsequently, the data were overlaid on the susceptibility map generated using the TRIGRS model. For this purpose, geological-geotechnical investigations were conducted both in the field and in the laboratory, encompassing the Standard Penetration Test (SPT), sample collection, and the determination of soil hydraulic conductivity and strength. The runoff of rainwater is considered the changes in the drainage network imposed by buildings and obstacles from human occupation. The modeling scenario considered the intense rainfall of May 2022, which caused landslides and flooding in RM-Recife. During this event, a rain gauge near the study area recorded 342 mm of rain over 96 hours. Several Landslides occurred, putting the lives of residents and the buildings at risk. Overlaying cadastral information, census data, and the susceptibility map made it possible to identify the distribution of geological risk in the sub-basin. The analyses contribute to the implementation of preventive and mitigation strategies and provide support for improving risk and disaster management. The Results are part of a CNPq project coordinated by GEGEP/UFPE, with CEMADEN and international cooperation with IRPI-CNR, aiming to enhance TRIGRS to incorporate relevant human actions into the analyses.