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GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China

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Abstract

Landslides have had a huge effect on human life, the environment and local economic development, and therefore they need to be well understood. In this study, we presented an approach for the analysis and modeling of landslide data using rare events logistic regression and applied the approach to an area in Lianyungang, China. Digital orthophotomaps, digital elevation models of the region, geological maps and different GIS layers including settlement, road net and rivers were collected and applied in the analysis. Landslides were identified by monoscopic manual interpretation and validated during the field investigation. To validate the quality of mapping, the data from the study area were divided into a training set and validation set. The result map showed that 4.26% of the study area was identified as having very high susceptibility to landslides, whereas the others were classified as having very low susceptibility (47.2%), low susceptibility (22.21%), medium susceptibility (14.39%) and high susceptibility (11.93%). The quality of the landslide-susceptibility map produced in this paper was validated, and it can be used for planning protective and mitigation measures. The landslide-susceptibility map is a fundamental part of the Lianyungang city landslide risk assessment.

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Acknowledgments

This study was supported by the National Natural Science Foundation of China (nos. 40801212 and 40871010), the National Natural Science Foundation of China (Key Project) (no. 40730527), the National Key Basic Research Program of the early special issues (no. 2007CB416602) and the Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection of Chendu University of Technology, China (no. GZ2007-11).

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Authors and Affiliations

  1. Key Laboratory of Virtual Geographic Environments (National Education Administration), College of Geographical Sciences, Nanjing Normal University, Nanjing, 210046, China

    Shibiao Bai, Guonian Lü, Jian Wang & Liang Ding

  2. China Institute of Geo-Environment Monitoring, Beijing, 100081, China

    Pinggen Zhou

Authors
  1. Shibiao Bai
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  2. Guonian Lü
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  3. Jian Wang
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  4. Pinggen Zhou
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  5. Liang Ding
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Correspondence to Shibiao Bai.

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Bai, S., Lü, G., Wang, J. et al. GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China. Environ Earth Sci 62, 139–149 (2011). https://doi.org/10.1007/s12665-010-0509-3

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