IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v43y2007i2p245-256.html
   My bibliography  Save this article

Use of satellite remote sensing data in the mapping of global landslide susceptibility

Author

Listed:
  • Yang Hong
  • Robert Adler
  • George Huffman

Abstract

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIS-based weighted linear combination method. First, six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor’s relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • Yang Hong & Robert Adler & George Huffman, 2007. "Use of satellite remote sensing data in the mapping of global landslide susceptibility," 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. 43(2), pages 245-256, November.
  • Handle: RePEc:spr:nathaz:v:43:y:2007:i:2:p:245-256
    DOI: 10.1007/s11069-006-9104-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-006-9104-z
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11069-006-9104-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andrea Fabbri & Chang-Jo Chung & Antonio Cendrero & Juan Remondo, 2003. "Is Prediction of Future Landslides Possible with a GIS?," 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. 30(3), pages 487-503, November.
    2. T. Fernández & C. Irigaray & R. El Hamdouni & J. Chacón, 2003. "Methodology for Landslide Susceptibility Mapping by Means of a GIS. Application to the Contraviesa Area (Granada, Spain)," 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. 30(3), pages 297-308, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Caruso, Germán Daniel, 2017. "The legacy of natural disasters: The intergenerational impact of 100 years of disasters in Latin America," Journal of Development Economics, Elsevier, vol. 127(C), pages 209-233.
    2. Juan Cao & Zhao Zhang & Jie Du & Liangliang Zhang & Yun Song & Geng Sun, 2020. "Multi-geohazards susceptibility mapping based on machine learning—a case study in Jiuzhaigou, China," 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(3), pages 851-871, July.
    3. Alexey Konovalov & Yuriy Gensiorovskiy & Andrey Stepnov, 2020. "Hazard-Consistent Earthquake Scenario Selection for Seismic Slope Stability Assessment," Sustainability, MDPI, vol. 12(12), pages 1-14, June.
    4. Dimitrios Myronidis & Charalambos Papageorgiou & Stavros Theophanous, 2016. "Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)," 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. 81(1), pages 245-263, March.
    5. S. Boussouf & T. Fernández & A. B. Hart, 2023. "Landslide susceptibility mapping using maximum entropy (MaxEnt) and geographically weighted logistic regression (GWLR) models in the Río Aguas catchment (Almería, SE Spain)," 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. 117(1), pages 207-235, May.
    6. Dimitris Kouhartsiouk & Skevi Perdikou, 2021. "The application of DInSAR and Bayesian statistics for the assessment of landslide susceptibility," 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(3), pages 2957-2985, February.
    7. Massimo Conforti & Gaetano Robustelli & Francesco Muto & Salvatore Critelli, 2012. "Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south Italy)," 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. 61(1), pages 127-141, March.
    8. Nussaïbah B. Raja & Ihsan Çiçek & Necla Türkoğlu & Olgu Aydin & Akiyuki Kawasaki, 2017. "Landslide susceptibility mapping of the Sera River Basin using logistic regression model," 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. 85(3), pages 1323-1346, February.
    9. A. Clerici & S. Perego & C. Tellini & P. Vescovi, 2010. "Landslide failure and runout susceptibility in the upper T. Ceno valley (Northern Apennines, Italy)," 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. 52(1), pages 1-29, January.
    10. Adel Ghasemi & Omid Bahmani & Samira Akhavan & Hamid Reza Pourghasemi, 2023. "Investigation of land-subsidence phenomenon and aquifer vulnerability using machine models and GIS technique," 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. 118(2), pages 1645-1671, September.
    11. Bipin Peethambaran & R. Anbalagan & K. V. Shihabudheen, 2019. "Landslide susceptibility mapping in and around Mussoorie Township using fuzzy set procedure, MamLand and improved fuzzy expert system-A comparative study," 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. 96(1), pages 121-147, March.
    12. Yan Du & Hui Liu & Heng Li & Mowen Xie & Santos D. Chicas & Jidong Wu & Fuxia Lv & Yaxin Wu, 2024. "Exploring the initiating mechanism, monitoring equipment and warning indicators of gully-type debris flow for disaster reduction: a review," 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. 120(15), pages 13667-13692, December.
    13. Vahed Ghiasi & Seyed Amir Reza Ghasemi & Mahyar Yousefi, 2021. "Landslide susceptibility mapping through continuous fuzzification and geometric average multi-criteria decision-making approaches," 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. 107(1), pages 795-808, May.
    14. Guilherme Garcia Oliveira & Luis Fernando Chimelo Ruiz & Laurindo Antonio Guasselli & Claus Haetinger, 2019. "Random forest and artificial neural networks in landslide susceptibility modeling: a case study of the Fão River Basin, Southern Brazil," 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. 99(2), pages 1049-1073, November.
    15. José Antonio Palenzuela & Jorge David Jiménez-Perálvarez & José Chacón & Clemente Irigaray, 2016. "Assessing critical rainfall thresholds for landslide triggering by generating additional information from a reduced database: an approach with examples from the Betic Cordillera (Spain)," 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. 84(1), pages 185-212, October.
    16. Dimitrios Myronidis & Charalambos Papageorgiou & Stavros Theophanous, 2016. "Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)," 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. 81(1), pages 245-263, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:43:y:2007:i:2:p:245-256. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.