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Shalstab mathematical model and WorldView-2 satellite images to identification of landslide-susceptible areas

Author

Listed:
  • Téhrrie König

    (National Institute for Space Research (INPE)
    National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN/MCTIC))

  • Hermann J. H. Kux

    (National Institute for Space Research (INPE))

  • Rodolfo M. Mendes

    (National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN/MCTIC)
    Vale do Paraíba University (UNIVAP/IP&D))

Abstract

Natural hazards, occurring all over the world, may become a disaster when humans and nature interact. In Brazil, landslides triggered by heavy rainfall are the most common phenomenon that affects the population. Due to the economic and social losses and deaths, the identification and monitoring of risk areas are extremely important. Therefore, this study aims to identify the landslide-susceptible areas in Vila Albertina and Britador neighborhood, located in Campos do Jordão city in São Paulo state, Brazil. Using the Shalstab mathematical model, which analyzes the slope stability, and satellite images from WorldView-2 sensor with data mining techniques, it was identified the most susceptible areas for this phenomenon and the main characteristics of human occupation that might induce landslides. To achieve this goal, three scenarios were simulated for each neighborhood, changing the values of the geotechnical parameters, used as input on Shalstab. The results of susceptibility areas were consistent with the reality observed in these neighborhoods and the landslide scars corroborate with the assumption that anthropic changes induce landslides. The satellite image allowed the identification of different types of human interaction and its changes in steep slope areas.

Suggested Citation

  • Téhrrie König & Hermann J. H. Kux & Rodolfo M. Mendes, 2019. "Shalstab mathematical model and WorldView-2 satellite images to identification of landslide-susceptible areas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(3), pages 1127-1149, July.
    • Handle: RePEc:spr:nathaz:v:97:y:2019:i:3:d:10.1007_s11069-019-03691-4
    DOI: 10.1007/s11069-019-03691-4
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    References listed on IDEAS

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    1. Roberto Gomes & Renato Guimarães & Osmar Carvalho & Nelson Fernandes & Eurípedes Vargas & Éder Martins, 2008. "Identification of the affected areas by mass movement through a physically based model of landslide hazard combined with an empirical model of debris flow," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 45(2), pages 197-209, May.
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    Cited by:

    1. Frederico F. Ávila & Regina C. Alvalá & Rodolfo M. Mendes & Diogo J. Amore, 2021. "The influence of land use/land cover variability and rainfall intensity in triggering landslides: a back-analysis study via physically based models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 1139-1161, January.
    2. I. Fustos & R. Abarca-del-Rio & P. Moreno-Yaeger & M. Somos-Valenzuela, 2020. "Rainfall-Induced Landslides forecast using local precipitation and global climate indexes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 102(1), pages 115-131, May.

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