Landslide susceptibility in Rio Grande do Sul: could past landslides indicate areas affected in May 2024?

Renata Pacheco Quevedo, Daniel Andrade Maciel, Clódis Oliveira Andrades-Filho, Lorenzo Fossa Sampaio Mexias, Guilherme Garcia de Oliveira, Pâmela Boelter Herrmann, Fabio Corrêa Alves, Thomas Glade

Publications: Contribution to conferencePaperPeer Reviewed

Abstract

The Mega Disaster that occurred in May 2024, reaching Rio Grande do Sul (RS), Brazil, resulted in more than 15,000 landslides, affecting nearly 18,000 km2. In this study, we generated a landslide susceptibility map based on historical landslide data (1995-2017) and assessed its capacity to forecast the 2024 landslides. Based on the Random Forest algorithm, we modelled landslide susceptibility for the entire RS with a high overall accuracy of 0.964. The retrospective evaluation using the 2024 landslide inventory considered two sets: i) polygon centroids, and ii) points by pixels. In the first approach, our model correctly classified 69% of the landslides in susceptible areas. The second analysis classified 31% of the points in very high susceptibility areas. Furthermore, when comparing the landslide areas, our model correctly classified most of the landslide rupture zones (79%). Finally, we highlight the need to consider landslide zones for updating susceptibility maps.
Original languageEnglish
Publication statusAccepted/In press - 2025
EventBrazilian Remote Sensing Symposium - Bahia, Salvador, Brazil
Duration: 13 Apr 202516 Apr 2025
Conference number: 21
https://2025.sbsr.com.br/sbsr-2025/page/4706-inicio?lang=en

Conference

ConferenceBrazilian Remote Sensing Symposium
Abbreviated titleSBSR
Country/TerritoryBrazil
CitySalvador
Period13/04/2516/04/25
Internet address

Austrian Fields of Science 2012

  • 105902 Natural hazards
  • 102019 Machine learning
  • 207402 Remote sensing

Keywords

  • natural hazard
  • disaster
  • Random Forest
  • modelling
  • Brazil

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