The influence of land use/land cover variability and rainfall intensity in triggering landslides: a back-analysis study via physically based models

Ávila, Frederico Fernandes de; Alvalá, Regina Célia dos Santos; Mendes, Rodolfo Moreda; Amore, Diogo

doi:10.1007/s11069-020-04324-x

Cited by 22 publications

(12 citation statements)

References 40 publications

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“…It is a physically-based digital terrain model for mapping slope stability potentially related to landslides [56]. Two publications compared some of these models and assessed their performance: Ávila et al [15] used TRIGRS and SF FIORI and concluded that TRIGRS leads to better results. Vieira et al [28] compared SHALSTAB and TRIGRS, and concluded that both models were effective in predicting landslides.…”

Section: Susceptibility Assessment Methodsmentioning

confidence: 99%

“…Vieira et al [28] compared SHALSTAB and TRIGRS, and concluded that both models were effective in predicting landslides. The first publication applying a slope stability model was published in 2010 [32], and the most recent was published in 2021 [15]. Statistical models are also commonly used, such as bivariate analysis, logistic regression, and fuzzy analysis.…”

Section: Susceptibility Assessment Methodsmentioning

confidence: 99%

“…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).…”

Section: Location Of Study Areasmentioning

confidence: 99%

“…König et al [27] is one example of publication that described the satellite image used: an image from the IKONOS satellite, dated April 2000, two months after the landslide event. Verification of the features during fieldwork was also commonly carried out by the authors [13,15,16,45,51].…”

Section: Origin Of the Landslide Inventorymentioning

confidence: 99%

“…In the quantitative approaches, homogeneous zones are created based on overlay maps and weighted factors with the application of statistical analysis, physically-based models, and machine learning techniques, rather than personal experience [14][15][16][17][18][19]. In general, quantitative approaches are used when detailed geotechnical information is not available for the whole study area, so the models recognize patterns through computation [8].…”

Section: Introductionmentioning

confidence: 99%

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Landslide Susceptibility Mapping in Brazil: A Review

2021

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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.

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Section: Susceptibility Assessment Methodsmentioning

confidence: 99%