Statistically-based regional landslide susceptibility assessment in the UNESCO global geopark Caminhos dos Cânions do Sul (Brazil)

Marina Tamaki de Oliveira Sugiyama (), José Eduardo Bonini (), Tiago Damas Martins (), Maria Carolina Villaça Gomes (), Susana Pereira () and Bianca Carvalho Vieira ()
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Marina Tamaki de Oliveira Sugiyama: University of São Paulo
José Eduardo Bonini: University of São Paulo
Tiago Damas Martins: Federal University of São Paulo (UNIFESP)
Maria Carolina Villaça Gomes: State University of Rio de Janeiro (UERJ)
Susana Pereira: University of Porto (UPorto)
Bianca Carvalho Vieira: University of São Paulo

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 15, No 8, 17439-17469

Abstract: Abstract The scenic value of landscapes within Geoparks is often attributed to the geomorphological processes that have shaped them in the past or up to the present day, including landslides. However, these processes also pose significant threats to the integrity of geosites and the safety of visitors, highlighting the need for risk prevention and mitigation plans for geohazards. The Caminhos dos Cânions do Sul Geopark (southern Brazil) lacks landslide inventories and susceptibility maps, essential for conducting practical geohazard risk analyses. This study addresses this gap by compiling a landslide inventory of the major events over the past 30 years, using a rule-based Object-Based Image Analysis (OBIA) approach, and assessing the susceptibility for four modeling domains within the Geopark using the Information Value method. Seven independent variables (aspect, slope, topographic wetness index, terrain ruggedness index, geomorphons, elevation, and curvature) were selected, resulting in 120 combinations for each modeling domain. For each predisposing factor combination, model performance was assessed using the area under the Receiver Operating Characteristics (ROC) curve, and the conditional independence of variables was evaluated. The best models for each domain were selected based on the criteria of conditional independence, goodness of fit, and number of variables. The final landslide susceptibility map was produced by merging the best three models’ results. The resulting susceptibility classification indicates that many geosites are located in areas with moderate to very high susceptibility or within zones likely to experience material transport or deposition.

Keywords: Global Geoparks Network; Serra Geral Escarpment; Object-based image analysis; Information value method (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07478-8

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