IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v50y2009i3p571-590.html
   My bibliography  Save this article

Building models for automatic landslide-susceptibility analysis, mapping and validation in ArcGIS

Author

Listed:
  • J. Jiménez-Perálvarez
  • C. Irigaray
  • R. El Hamdouni
  • J. Chacón

Abstract

In this paper, ModelBuilder TM in ArcGIS (ESRI) has been applied to landslide-susceptibility analysis, mapping and validation. The models (scripts), available for direct downloading as an ArcGIS tool, allow landslide susceptibility to be computed in a given region, providing a landslide-susceptibility map, with the GIS matrix method, and ensuring a quality validation. The paper details the steps needed for the model-building process, enabling users to build their own models and to become more familiar with the tool. The susceptibility model leads the user first through a Digital Elevation Model (DEM), depicting the morphological and morphometric features of the study area, and then through a Digital Terrain Model (DTM), useful as a source of landslide-determinant factors, such as slope elevation, slope angle and slope aspect. In addition, another determinant factor is the lithological unit, independent of the DEM. Once the determinant landslide factors are reclassified and in a vectorial format, all the combinations between the classes of these factors are determined using the geoprocessing abilities of ArcGIS. The next step for the development of the landslide-susceptibility model consists of identifying the areas affected by a given surface of rupture (i.e. source area) in every combination of the determinant-factor classes. This step leads to the landslide matrix based on a previously georeferenced landslide database of the region, in which the slopes are distinguished into two simple classes: with or without landslides. In the last stage, to build a landslide-susceptibility model, the user computes the percentages of area affected by landslides in every combination of determinant factors. In the resulting landslide-susceptibility map a progressive zonation of areas or slopes increasingly prone to landslides is performed. A model for the validation of the resulting landslide-susceptibility map is also presented, based on the determination of the degree of fit, which is calculated from the cross tabulation between a set of landslides (not included in the susceptibility analysis) and the corresponding susceptibility map. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • J. Jiménez-Perálvarez & C. Irigaray & R. El Hamdouni & J. Chacón, 2009. "Building models for automatic landslide-susceptibility analysis, mapping and validation in ArcGIS," 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. 50(3), pages 571-590, September.
    • Handle: RePEc:spr:nathaz:v:50:y:2009:i:3:p:571-590
    DOI: 10.1007/s11069-008-9305-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-008-9305-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-008-9305-8?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. Juan Remondo & Alberto González & José De Terán & Antonio Cendrero & Andrea Fabbri & Chang-Jo Chung, 2003. "Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern 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 437-449, November.
    2. Chang-Jo Chung & Andrea Fabbri, 2003. "Validation of Spatial Prediction Models for Landslide Hazard Mapping," 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 451-472, November.
    3. Clemente Irigaray & Francisco Lamas & Rachid El Hamdouni & Tomás Fernández & José Chacón, 2000. "The Importance of the Precipitation and the Susceptibility of the Slopes for the Triggering of Landslides Along the Roads," 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. 21(1), pages 65-81, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Yang, Yu & He, Ze & Song, Zouying & Fu, Xin & Wang, Jianwei, 2018. "Investigation on structural and spatial characteristics of taxi trip trajectory network in Xi’an, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 755-766.
    3. Marta Fernandez-Hernández & Carlos Paredes & Ricardo Castedo & Miguel Llorente & Rogelio la Vega-Panizo, 2012. "Rockfall detachment susceptibility map in El Hierro Island, Canary Islands, 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. 64(2), pages 1247-1271, November.

    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. D. Costanzo & C. Cappadonia & C. Conoscenti & E. Rotigliano, 2012. "Exporting a Google Earth ™ aided earth-flow susceptibility model: a test in central Sicily," 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 103-114, March.
    2. E. Rotigliano & C. Cappadonia & C. Conoscenti & D. Costanzo & V. Agnesi, 2012. "Slope units-based flow susceptibility model: using validation tests to select controlling factors," 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 143-153, March.
    3. Massimo Conforti & Pietro Aucelli & Gaetano Robustelli & Fabio Scarciglia, 2011. "Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, 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. 56(3), pages 881-898, March.
    4. 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.
    5. C. Irigaray & T. Fernández & R. El Hamdouni & J. Chacón, 2007. "Evaluation and validation of landslide-susceptibility maps obtained by a GIS matrix method: examples from the Betic Cordillera (southern 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. 41(1), pages 61-79, April.
    6. 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.
    7. G. Chevalier & V. Medina & M. Hürlimann & A. Bateman, 2013. "Debris-flow susceptibility analysis using fluvio-morphological parameters and data mining: application to the Central-Eastern Pyrenees," 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. 67(2), pages 213-238, June.
    8. Omid Rahmati & Ali Haghizadeh & Hamid Reza Pourghasemi & Farhad Noormohamadi, 2016. "Gully erosion susceptibility mapping: the role of GIS-based bivariate statistical models and their comparison," 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. 82(2), pages 1231-1258, June.
    9. E. Rotigliano & V. Agnesi & C. Cappadonia & C. Conoscenti, 2011. "The role of the diagnostic areas in the assessment of landslide susceptibility models: a test in the sicilian chain," 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. 58(3), pages 981-999, September.
    10. Jaime Bonachea & Juan Remondo & José Ramón Díaz De Terán & Alberto González‐Díez & Antonio Cendrero, 2009. "Landslide Risk Models for Decision Making," Risk Analysis, John Wiley & Sons, vol. 29(11), pages 1629-1643, November.
    11. Anna Małka, 2021. "Landslide susceptibility mapping of Gdynia using geographic information system-based statistical 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. 107(1), pages 639-674, May.
    12. Bosy A. El-Haddad & Ahmed M. Youssef & Hamid R. Pourghasemi & Biswajeet Pradhan & Abdel-Hamid El-Shater & Mohamed H. El-Khashab, 2021. "Flood susceptibility prediction using four machine learning techniques and comparison of their performance at Wadi Qena Basin, Egypt," 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 83-114, January.
    13. Francesca Vergari, 2015. "Assessing soil erosion hazard in a key badland area of Central 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. 79(1), pages 71-95, November.
    14. Francisco Gutiérrez & Jesús Guerrero & Pedro Lucha, 2008. "Quantitative sinkhole hazard assessment. A case study from the Ebro Valley evaporite alluvial karst (NE 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. 45(2), pages 211-233, May.
    15. Kourosh Shirani & Mehrdad Pasandi & Alireza Arabameri, 2018. "Landslide susceptibility assessment by Dempster–Shafer and Index of Entropy models, Sarkhoun basin, Southwestern Iran," 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. 93(3), pages 1379-1418, September.
    16. Cristina Tarantino & Palma Blonda & Guido Pasquariello, 2007. "Remote sensed data for automatic detection of land-use changes due to human activity in support to landslide studies," 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. 41(1), pages 245-267, April.
    17. Bin Ou-Yang & Chun-Chao Chu & Ya-Bin Da & Xiao-Fei Liu & Hai-Ying Zhang, 2015. "Highway flood disaster risk evaluation and management in 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. 75(2), pages 381-397, February.
    18. Netra Bhandary & Ranjan Dahal & Manita Timilsina & Ryuichi Yatabe, 2013. "Rainfall event-based landslide susceptibility zonation mapping," 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. 69(1), pages 365-388, October.
    19. Kamila Pawluszek & Andrzej Borkowski, 2017. "Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland," 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. 86(2), pages 919-952, March.
    20. Alejandro Gonzalez-Ollauri & Slobodan B. Mickovski, 2021. "A Simple GIS-Based Tool for the Detection of Landslide-Prone Zones on a Coastal Slope in Scotland," Land, MDPI, vol. 10(7), pages 1-15, June.

    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:50:y:2009:i:3:p:571-590. 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.