A comparative study on the landslide susceptibility mapping using logistic regression and statistical index models

  • Zhiyong Wu
  • Yanli Wu
  • Yitian Yang
  • Fuwei Chen
  • Na Zhang
  • Yutian Ke
  • Wenping Li
Original Paper


The logistic regression and statistical index models are applied and verified for landslide susceptibility mapping in Daguan County, Yunnan Province, China, by means of the geographic information system (GIS). A detailed landslide inventory map was prepared by literatures, aerial photographs, and supported by field works. Fifteen landslide-conditioning factors were considered: slope angle, slope aspect, curvature, plan curvature, profile curvature, altitude, STI, SPI, and TWI were derived from digital elevation model; NDVI was extracted from Landsat ETM7; rainfall was obtained from local rainfall data; distance to faults, distance to roads, and distance to rivers were created from a 1:25,000 scale topographic map; the lithology was extracted from geological map. Using these factors, the landslide susceptibility maps were prepared by LR and SI models. The accuracy of the results was verified by using existing landslide locations. The statistical index model had a predictive rate of 81.02%, which is more accurate prediction in comparison with logistic regression model (80.29%). The models can be used to land-use planning in the study area.


Landslide Susceptibility Logistic regression Statistical index China 



The authors thank the National Basic Research Program of China “973” (No. 2015CB251601), the People’s Livelihood Research Project of Hebei Province (201301211), and the Research Fund for the Scientific Studies in Higher Education Institutions of Hebei Province (QN2015306) for the financial support. Also, the authors would like to express their gratitude to the anonymous reviewers for their constructive comments and suggestions, which highly increased the quality of the paper.


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Copyright information

© Saudi Society for Geosciences 2017

Authors and Affiliations

  • Zhiyong Wu
    • 1
    • 2
  • Yanli Wu
    • 1
    • 3
  • Yitian Yang
    • 2
  • Fuwei Chen
    • 4
  • Na Zhang
    • 2
  • Yutian Ke
    • 5
  • Wenping Li
    • 1
  1. 1.School of Resources and GeoscienceChina University of Mining and TechnologyXuzhouChina
  2. 2.College of Resource and Environmental SciencesHebei Normal University for NationalitiesChengdeChina
  3. 3.Exploration & Surveying Division, Northwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting GroupXi’anChina
  4. 4.Science Research DepartmentHebei Normal University for NationalitiesChengdeChina
  5. 5.School of Civil Engineering and MechanicsLanzhou UniversityLanzhouChina

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