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Open AccessArticle

Refinement of Landslide Susceptibility Map Using Persistent Scatterer Interferometry in Areas of Intense Mining Activities in the Karst Region of Southwest China

1
Precision Forestry Key Laboratory of Beijing, Beijing Forestry University, Beijing 100083, China
2
The Third Surveying and Mapping Institute of Guizhou Province, Guiyang 550004, China
3
Key Laboratory of Microwave Objective Characteristics and Remote Sensing in Zhejiang Province, Zhongke Satellite Application Deqing Academy, Deqing 313200, China
4
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
5
China Electric Power Research Institute Co., Ltd., Beijing 100055, China
6
School of Earth Sciences and Resources China University of Geosciences, Beijing 100083, China
7
School of Civil Engineerin, Beijing jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(23), 2821; https://doi.org/10.3390/rs11232821
Received: 5 November 2019 / Accepted: 24 November 2019 / Published: 28 November 2019
(This article belongs to the Special Issue Remote Sensing of Landslides II)
Incremental vertical ground movements due to coal mining can increase landslide susceptibility greatly in a short time and have thus triggered a large number of geological disasters, especially in the Karst Region, where a lot of steep slopes are on fractured rocks. Therefore, the landslide susceptibility maps (LSM) in Karst Region should be updated regularly. This paper presents an efficient methodology to update and refine LSM by using Persistent Scatterer Interferometry (PSI) data directly. First, an original LSM was produced by using a support vector machine (SVM) algorithm, and the distribution of coal mining was considered a crucial factor to generate the LSM. Then, the Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique was implemented to retrieve displacement time-series. Finally, the landslide displacement map, produced by the PSInSAR analysis, was projected to the direction of the steepest slope and resampled to the same cell in the LSM, to update the original LSM. This methodology is illustrated with the case study of Bijie in the Karst Region of Southwest China, wherein the ascending RADARSAT-2 and descending Sentinel-1 datasets are processed for the period of 2017–2019. The results show that the susceptibility degree increased in 56.41 km2 of the study area, and 80 percent of the increased susceptibility degree was caused by coal mining. The comparison between original and refined LSM in two specific areas revealed that the proposed method can produce more-reliable landslide susceptibility maps in areas of intense mining activities in the Karst Region. View Full-Text
Keywords: landslide susceptibility; Persistent Scatterer Interferometry; intense mining activities; Karst Region landslide susceptibility; Persistent Scatterer Interferometry; intense mining activities; Karst Region
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MDPI and ACS Style

Shen, C.; Feng, Z.; Xie, C.; Fang, H.; Zhao, B.; Ou, W.; Zhu, Y.; Wang, K.; Li, H.; Bai, H.; Mannan, A.; Chen, P. Refinement of Landslide Susceptibility Map Using Persistent Scatterer Interferometry in Areas of Intense Mining Activities in the Karst Region of Southwest China. Remote Sens. 2019, 11, 2821.

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