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Landslide spatial susceptibility mapping by using GIS and remote sensing techniques: a case study in Zigui County, the Three Georges reservoir, China

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Abstract

Landslides are one of the most destructive phenomena in nature and damage both property and lives every year. In this paper, a logistic regression model with datasets developed via a geographic information system and remotely sensed data was used to create a landslide spatial susceptibility map for the Three Gorges Project reservoir region on the Yangtze River in Zigui County. The five causative factors used in the logistic regression model were evaluated in different ways: topographic slope and topographic aspect were derived from a topographical map at 1:50,000 scale; bed rock-slope relationship and lithology were obtained from a geological map at 1:50,000 scale; and fractional vegetation cover (FVC), which represents the reduced frequency of landslides due to the vegetation canopy and ground cover and is also one of the most difficult parameters to estimate over broad geographic areas, was generated using a back propagation neural network (BPNN) method based on CBERS (China–Brazil Earth Resources Satellite) data, the results of which were compared with values measured in the field. The obtained Pearson correlation coefficient (r) was 0.899. Then, the FVC factor and the other four factors were used as the input to a logistic regression model. By integrating the five factor maps in the geographical information system (GIS) via pixel-based computing, the landslide spatial susceptibility map was obtained. The study area was reclassified into four categories of landslide susceptibility: severe, moderate, low, and very low. Approximately 15.0 % of the study area was identified as severe susceptibility, and very low, low, and moderate susceptibility zones covered 21.8, 41.7, and 21.5 % of the area, respectively. These results have an accuracy of 78.90 %. Thus, by using a logistic regression model in a GIS environment, a spatial susceptibility map of landslides can be obtained, and the regions in Zigui County that are susceptible to landslides and need immediate protective and mitigation measures can be identified.

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Acknowledgments

This research was funded by the CRSRI Open Research Program (CKWV2013221/KY), the Special Fund for Basic Scientific Research of Central Colleges, China University of Geosciences (Wuhan) (CUGL100206), the Natural Science Foundation of Hubei Province (2012FFB06501), the Open Research Fund Program of Key Laboratory of Digital Mapping and Land Information Application Engineering, State Bureau of Surveying and Mapping (GCWD201202), the Open Research Fund of Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (2011LDE003), the National High Technology Research and Development Program of China (2012AA121303), and the National Natural Science Foundation of China (61102128).

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Authors and Affiliations

  1. Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, People’s Republic of China

    Tao Chen, Ruiqing Niu & Yi Wang

  2. Computer School, Wuhan University, Wuhan, People’s Republic of China

    Bo Du

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  1. Tao Chen
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Correspondence to Tao Chen.

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Chen, T., Niu, R., Du, B. et al. Landslide spatial susceptibility mapping by using GIS and remote sensing techniques: a case study in Zigui County, the Three Georges reservoir, China. Environ Earth Sci 73, 5571–5583 (2015). https://doi.org/10.1007/s12665-014-3811-7

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