Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast

Landslide Susceptibility Mapping in Brazil: A Review

“…The first paper that used statistical models for landslide susceptibility mapping in our database was from 2019 [16]. The authors compared several statistical approaches (Bayesian model, informative value, weights of evidence, logistic regression, and discriminant analysis), and the most recent papers that applied these methods were published in 2021 [25,40]. One publication compared the SHALSTAB model and the informative value approach in São Paulo state.…”

“…The first paper that applied statistical validation methods was published in 2015 [52]. Between 2015 and 2021, 27 articles were published and 15 out of them applied cross tabulation [36,52], success curve [26], AUC [14,16,25,35,40,42], ROC [43,46], or AUC/ROC [15,34,44,45] to validate the susceptibility maps. Two publications mentioned validation curves, but did not provide details about them [13,50].…”

“…The study areas of each publication were analyzed based on the federal state of occurrence. Out of the 33 studies analyzed, 19 of them were in the southeast region, in the states of São Paulo (10) [15,[25][26][27][28][29][30][31][32][33], Rio de Janeiro (7) [12,[34][35][36][37][38][39], Minas Gerais (2) [16,40], and Espírito Santo (1) [41]. The remaining 14 were in the south region, in Rio Grande do Sul (8) [14,35,[42][43][44][45][46][47], Santa Catarina (4) [13,[48][49][50], and Paraná (2) [51,52] (Figure 3).…”

Differences in the occurrence of debris flows in tropical and temperate environments: field observations and geomorphologic characteristics in Serra do Mar (Brazil) and British Columbia (Canada)

“…Over the last 60 years, the recorded number of debris flows and shallow landslides has become more frequent in Brazil, including in the Serra do Mar Mountains and on the south and southeast coasts. Remarkable disastrous events occurred in Caraguatatuba (1967), Rio de Janeiro Mountain range and Serra da Prata (2011), and Itaoca (2014), causing economic and social losses and stressing the need for mitigation measures, as well as a susceptibility assessment (Ploey and Cruz 1979, JICA 1991, Coelho-Netto et al 2013, Gomes and Vieira 2016, Facuri and Picanço 2020, Lima et al 2020, Dias et al 2021a). These events caused social damage (more than 3,000 deaths) and economic losses (at least $3 billion (USD)) (World Bank 2014, Kanji et al 2017).…”

Editorial: Physics and modelling of landslides

“…However, the causative factors and mechanisms underlying landslide initiation and dynamics must be better understood, as accurate modelling of landslide risk is an essential prerequisite for developing reliable control and mitigation strategies [1]. Landslide susceptibility is influenced by a broad range of factors [2], such as soil physics and geochemistry, geological setting, climate, atmospheric dynamics, biogenic feedbacks, and anthropogenic influences, which have profound interlinkages with each other over a broad period-and length-scales. Moreover, landslide risk assessment further hinges on correctly understanding communities ' local vulnerability and exposure [3].This Research Topic of articles on the Physics and Modelling of Landslides presents leadingedge work into the quantitative understanding of landslide processes and dynamics.A series of numerical simulations were carried out by Wang et al for a better understanding of the dynamic response and failure modes of rock slopes containing weak interlayers subjected to earthquake excitation.…”