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Landslide susceptibility mapping with the integration of information theory, fractal theory, and statistical analyses at a regional scale: a case study of Altay Prefecture, China

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Abstract

Due to the complex geo-environmental process, natural disasters often present heterogenous characters at different scales. As a stochastic and chaotic natural phenomenon, landslide generally shows fractal spatial distribution. In this paper, we proposed an integrated method combining fractal theory, information theory, and statistical analyses for landslide susceptibility mapping (LSM) at regional scales. The two primary contributions of this study can be summarized as follows. First, the spatial association between landslide occurrences and conditional factors is quantitatively measured by introducing the variable fractal dimension method (VFDM). Second, to overcome the uncertainties and subjectivities in VFDM, Shannon’s entropy index is introduced to determine the optimal class number of each conditional factor. To our best knowledge, this paper reports the first time that an integration method of fractal theory and information theory is used for LSM. The proposed method is illustrated and verified by an example in Altay Prefecture, NW China. In the example, historical landslides data were randomly split into a training data set and a validating data set with a 7:3 ratio. Seven factors recognized as correlated to landslides (lithology, distance to fault, altitude, slope, aspect, distance to stream, and distance to the road) were processed and analyzed in the geographic information system. The predictive accuracy of the method was evaluated using the area under the receiver operating curve (AUROC). The example demonstrates that the proposed method provides a good and reliable prediction for the study area (AUROC = 0.8467).

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Funding

The authors would like to thank the Editor-in-Chief and anonymous reviewers for their helpful and insightful comments to improve the manuscript. This research was funded by Science and Technology Project of China Highway Engineering Consulting Corporation (No. zzkj-2017).

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  1. China Highway Engineering Consulting Corporation, Beijing, 10089, China

    Xiaolong Deng, Guangji Sun, Naiwu He & Yonghua Yu

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  1. Xiaolong Deng
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  2. Guangji Sun
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  3. Naiwu He
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  4. Yonghua Yu
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Correspondence to Xiaolong Deng.

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Deng, X., Sun, G., He, N. et al. Landslide susceptibility mapping with the integration of information theory, fractal theory, and statistical analyses at a regional scale: a case study of Altay Prefecture, China. Environ Earth Sci 81, 346 (2022). https://doi.org/10.1007/s12665-022-10470-1

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