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A geospatial information quantity model for regional landslide risk assessment

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  • Yumin Tan
  • Dong Guo
  • Bo Xu

Abstract

Using geospatial technologies to assess geological hazard risk has been proved feasible and effective. In this paper, a geospatial information quantity model is proposed to assess landslide risk, which includes nine triggering factors: slope, aspect, cumulative catchment area, formation lithology, seismic intensity, distances to water, precipitation, vegetation, and land use/land cover type, in which the last three triggers are dynamic ones and need to be extracted from up-to-date remote sensing images. These triggering factors are then taken as geospatial information quantities and used to construct an information quantity-based model to assess and predict the landslides in Fuling District, Chongqing City, China, resulting in a risk distribution map. Finally, ROC curve is used to validate the model. With the AUC of success-rate ROC of 0.839 and the AUC of prediction-rate ROC of 0.807, the model is proved reliable to interpret and predict the landslide occurrences in the study area. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Yumin Tan & Dong Guo & Bo Xu, 2015. "A geospatial information quantity model for regional landslide risk assessment," 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(2), pages 1385-1398, November.
    • Handle: RePEc:spr:nathaz:v:79:y:2015:i:2:p:1385-1398
    DOI: 10.1007/s11069-015-1909-1
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    References listed on IDEAS

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    1. Dieu Bui & Owe Lofman & Inge Revhaug & Oystein Dick, 2011. "Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression," 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. 59(3), pages 1413-1444, December.
    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.
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