Combined PS-InSAR Technology and High-Resolution Optical Remote Sensing for Identifying Illegal Underground Mining in the Suburb of Yangquan City, Shanxi Province, China

Author:

Xia Yuanping1,Xia Fei2,Hui Zhenyang1,Li Huaizhan3ORCID,Wan Ranran4,Ai Jinquan1

Affiliation:

1. School of Surveying and Geoinformation Engineering, East China University of Technology (ECUT), Nanchang 330013, China

2. School of Earth Sciences, East China University of Technology (ECUT), Nanchang 330013, China

3. NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology (CUMT), Xuzhou 221116, China

4. Jiangxi Institute of Land Space Survey and Planning, Nanchang 330025, China

Abstract

Illegal mining is one of the biggest problems in many coal mines. With the rapid development of the economy, driven by huge economic benefits, some outlaws illegally exploit mineral resources without a mining license, which is destructive and a potential safety hazard. In order to avoid inspection by law enforcement officials, some outlaws, regardless of the cost or risk, privately and surreptitiously excavate coal mines in self-built houses. The coal resources they excavate are shallow coal resources. Because surface buildings can maintain strong and stable radar scattering characteristics over a long time series, in this study, we combined PS-InSAR technology and high-resolution optical remote sensing to extract the subsidence information of surface buildings corresponding to PS point sets and analyzed their spatiotemporal characteristics. Finally, we developed a fast and accurate method for detecting suspected illegal mining sites from building subsidence information over a larger area. We also carried out a case study using Shandi Village, a suburb of Yangquan City, Shanxi Province, China, as our research object. QuickBird-2, WorldView-2 data, and 20 PALSAR scenes were selected for the experimental research, and two illegal mining sites were detected from 29 December 2006 to 9 January 2011. By comparing our results with previous investigation data, it was found that the accuracy rate reached 40% in local areas, and the detection rate reached 66.67%. In addition, the mining periods were basically consistent. This research shows that our method is feasible and has certain engineering applicability and practical value.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference24 articles.

1. Zhao, X., and Jiang, X. (2005, March 12). Coal Mining: Most Deadly Job in China [EB]. Available online: http://www.chinadaily.com.cn/english/doc/2004-11/13/content_391242.htm.

2. Monitoring of Mining Order in Shenfu Coal Based on RS and GIS;Zhou;Geospat. Inf.,2013

3. Research on Application of Remote Sensing Investigation and Monitoring of Mine Development Based on High Resolution Image;Jia;West. Resour.,2016

4. Remote Sensing Study on the Relationship between Cross-border Mining and Mining Rights Area;Liu;Geospat. Inf.,2019

5. Yang, X. (2015). Research and Implementation on Location Monitoring Algorithm for Mining Cross-Border Areas, Guilin University of Electronic Technology.

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