Landslide Susceptibility Mapping in Brazil: A Review

Autor(es)

Dias, Helen Cristina ^[1] ; Hoelbling, Daniel ^[2] ; Grohmann, Carlos Henrique ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Energy & Environm, BR-05508010 Sao Paulo - Brazil

^[2] Salzburg Univ, Dept Geoinformat ZGIS, A-5020 Salzburg - Austria

• Tipo de documento: Artigo de Revisão
• Fonte: GEOSCIENCES; v. 11, n. 10 OCT 2021.
• Citações Web of Science: 0

Resumo

Landslide susceptibility studies are a common type of landslide assessment. Landslides are one of the most frequent hazards in Brazil, resulting in significant economic and social losses (e.g., deaths, injuries, and property destruction). This paper presents a literature review of susceptibility mapping studies in Brazil and analyzes the methods and input data commonly used. The publications used in this analysis were extracted from the Web of Science platform. We considered the following aspects: location of study areas, year and where the study was published, methods, thematic variables, source of the landslide inventory, and validation methods. The susceptibility studies are concentrated in Brazil's south and southeast region, with the number of publications increasing since 2015. The methods commonly used are slope stability and statistical models. Validation was performed based on receiver operating characteristic (ROC) curves and area under the curve (AUC). Even though landslide inventories constitute the most critical input data for susceptibility mapping, the criteria used for the creation of landslide inventories are not evident in most cases. The included studies apply various validation techniques, but evaluations with potential users and information on the practical applicability of the results are largely missing.</p> (AU)

• Processo FAPESP: 19/17261-8 - Análise de Inventário manuais e semi-automáticos de escorregamentos rasos e sua adequabilidade para utilização em modelos preditivos
• Beneficiário: Helen Cristina Dias
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 19/26568-0 - Sensoriamento remoto de alta resolução, deep learning e geomorfometria em análise de deslizamentos naturais e risco geológico
• Beneficiário: Carlos Henrique Grohmann de Carvalho
• Modalidade de apoio: Auxílio à Pesquisa - Regular