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

Abstract

Statistical susceptibility assessment is a common approach applied worldwide for shallow landslide studies. Identification of morphological and geological conditions is essential and still incipient to evaluate the susceptibility of landslide events in the Brazilian territory. This study aimed to develop and compare shallow landslide susceptibility scenarios based on a bivariate statistical evaluation of geological (lithology and structures) and morphological (curvature, elevation, slope, and aspect) factors in Caraguatatuba, northern coast of São Paulo State in Brazil. A compilation of geological factors from published maps was made, and morphological maps were created based on Shuttle Radar Topography Mission (30 m). A bivariate statistical application by the informative value method was used to create four susceptibility scenarios, and the validation was achieved using the area under the curve (AUC). The results indicated that lithology was the more relevant conditioning factor, followed by elevation and slope. The methodology used to determine the susceptibility was efficient (AUC values between 0.809 and 0.841). The susceptibility scenario comparison identified that conditioning factors with the highest informational value generated the most accurate mapping. This indicates that using several conditioning factors does not necessarily generate a better map. This study contributes to shallow landslides research from a methodological perspective, as it is the first analysis of its kind in Serra do Mar Paulista, which are continuously affected by mass movements. Open-source data were chosen to be used, focusing on methodological applicability in other regions of the country, since resources for landslide studies in Brazil are low.

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Acknowledgements

This work was supported primarily by the National Council for Scientific and Technological Development (CNPq, Grant #138162/2016-6), by the Graduate Program in Physical Geography of the University of São Paulo, and FAPESP (Grant #2019/17261-8). CHG is a research fellow of CNPq (Grants #304413/2018-6 and #423481/2018-5). This study was financed in part by CAPES Brasil—Finance Code 001. We would like to acknowledge the Institute of Technical Research of the State of São Paulo (IPT) for giving us the possibility of participating in the “New Talents” program and to the Editor-in-Chief and the anonymous reviewers for their criticism and suggestions, which have helped to improve this paper.

Funding

This work was supported by the National Council for Scientific and Technological Development (CNPq, Grant #138162/2016-6) and financed in part by CAPES Brasil—Finance Code 001 and FAPESP (Grant #2019/17261-8).

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HCD contributed to conceptualization of this study, data collection and processing, writing—original draft preparation, analysis, discussions, and writing—review and editing; MFG contributed to data collection, analysis, discussions, and writing—review and editing; CHG contributed to writing—review and editing; CB contributed to analysis, discussions, data processing, and writing—review and editing. BCV contributed to supervision, analysis, discussions, and writing—review and editing.

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Correspondence to Helen Cristina Dias.

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The raw data required in this study are available upon request by contacting H. C. Dias (helen.dias@usp.br).

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Dias, H.C., Gramani, M.F., Grohmann, C.H. et al. Statistical-based shallow landslide susceptibility assessment for a tropical environment: a case study in the southeastern Brazilian coast. Nat Hazards 108, 205–223 (2021). https://doi.org/10.1007/s11069-021-04676-y

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  • DOI: https://doi.org/10.1007/s11069-021-04676-y

Keywords

  • Informative value
  • Mass movement
  • Serra do Mar
  • Statistical index method
  • AUC