Enhancing Landslide Susceptibility with LiDAR in São Sebastião

São Sebastião, a municipality on the coast of São Paulo state in Brazil that was partially cut off from the rest of the country in February 2023 after a period of torrential rain, had more than 1,000 landslide points, according to an inventory produced by researchers at the University of São Paulo’s Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG-USP) and Institute of Geosciences (IGc-USP) using aerial images collected shortly after the disaster. Predicting landslide susceptibility in this region is being supported with the use of lidar imagery in a new research project.

From an article in Phys.org by Luciana Constantino.

The inventory that mapped landslide risks in the municipality is published in the Brazilian Journal of Geology.

The scientists are now analyzing higher-resolution LIDAR images to find out how the inventory correlates with other variables and to develop a method for mapping the risk of landslides more precisely. LIDAR (Light Detection and Ranging) is an airborne remote sensing method that uses light in the form of a pulsed laser to generate precise 3D images of the Earth’s surface.

“In this type of analysis, known as a landslide susceptibility assessment, knowledge of the areas in which landslides occurred, including topographical, geological and other data, is extrapolated for other areas.

“We currently have digital elevation models with a spatial resolution [pixel size] of 30 m. The LIDAR data lets us go a step farther and apply elevation models with higher resolution [as high as 1 m] and more precision,” Carlos Henrique Grohmann, full professor at IAG-USP, told Agência FAPESP.

Grohmann is the leader of the project and involves a partnership with the São Paulo State Institute of Geography and Cartography (IGC-SP, an arm of the Department of Budget and Administration). The institute is creating a repository of LIDAR images for the entire state. This is the first time the scientific community has had access to LIDAR data for the Serra do Mar region.

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