Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/nhess-2016-347
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
03 Nov 2016
Review status
A revision of this discussion paper is under review for the journal Natural Hazards and Earth System Sciences (NHESS).
Landslide susceptibility mapping on global scale using method of logistic regression
Le Lin1,2, Qigen Lin1,2, and Ying Wang1,2 1Key Laboratory of Environmental Change and Natural Disaster of MOE, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, 100875, Beijing, China
2Academy of Disaster Reduction and Emergency Management, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, 100875, Beijing, China
Abstract. This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected to model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building model, 70 % of landslide and non-landslide points were randomly selected for logistic regression, and the others were used for model validation. For evaluating the accuracy of predictive models, this paper adopts several criteria including receiver operating characteristic (ROC) curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC) was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

Citation: Lin, L., Lin, Q., and Wang, Y.: Landslide susceptibility mapping on global scale using method of logistic regression, Nat. Hazards Earth Syst. Sci. Discuss., doi:10.5194/nhess-2016-347, in review, 2016.
Le Lin et al.
Le Lin et al.
Le Lin et al.

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Short summary
To address the issue that what can influence the occurrence of landslides in global scale and to which extend those factors can have, in a relatively objective way, we proposed to produce a global landslide susceptibility map using the method of logistic regression. We find out that topology may not be the first controlling factor of landslides and finer resolution of DEM may not significantly contribute to the improvement of landslide model when location precision of landslides is limited.
To address the issue that what can influence the occurrence of landslides in global scale and to...
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