Spatiotemporal changes of illegal mining in Hunan mines based on multi-source satellite remote sensing

被引：0
|
作者：
Liu L. [1 ,2 ,3 ]
Li C. [1 ]
Gao J. [3 ]
Yu L. [1 ,3 ]
Liu S. [3 ]
机构：
[1] School of Earth Sciences, China University of Geosciences, Wuhan
[2] Hunan Provincial Geological Museum, Changsha
[3] Hunan Remote Sensing Center, Changsha
来源：
National Remote Sensing Bulletin | 2022年 / 26卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Hunan; Illegal mining; Kriging; Mine; Multi-source remote sensing; Spatiotemporal changes;
D O I：
10.11834/jrs.20219284
中图分类号：
学科分类号：
摘要：
In recent years, the unreasonable development and utilization of mineral resources have been a global concern, and studying the spatial and temporal distribution characteristics of illegal mining resources is of particular importance. To solve the difficulty in obtaining information on the illegal mining of large-scale mineral resources, low accuracy, scattered data, and lack of long time series, this paper proposes a method for extracting the spatiotemporal distribution characteristics of illegal mining in multi-source satellite remote sensing data. First, Hunan Province was used as the research area, and the multi-source satellite remote sensing image data of 2010-2017 were combined with the mining rights data of Hunan Province. The human-machine interactive interpretation method was used to extract the illegal mining data of 2010-2017. The Kriging spatial data interpolation method analyzes the mining illegal mining data for 8 years. Finally, on this basis, the spatial and temporal distribution characteristics of illegal mining in Hunan Province are mainly studied. Results show that from 2010 to 2017, Hunan Province had a total of 2815 illegal mines, which were mainly distributed in Southern Hunan, Southwestern Hunan, Central Hunan, and Eastern Hunan, showing a year-on-year rising trend in time. Xiangnan, Xiangxi, Xiangdong, Xiangbei, and Northwestern Hunan expand and change in stages and regions. The spatial distribution also tends to develop from "high concentration" to "multiple points and wide areas." Illegal mining is mainly based on non-metallic mines. A certain number of energy and metal mines exists. The illegal mining of non-metal mines shows a significant upward trend; the types of illegal mining are mainly unlicensed and cross-border mining, and the behavior of cross-border mining is on the rise. This study shows that the use of multi-source satellite remote sensing data can objectively, accurately, and long-term extract large-scale mining illegal information and effectively reveal the spatial and temporal distribution characteristics of illegal mining. An in-depth study of the driving force of illegal mining behavior is provided. Scientific and theoretical bases are provided for the country to formulate adaptive policies. © 2022, Science Press. All right reserved.
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页码：528 / 540
页数：12
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共 45 条
  • [1] Armstrong M., Basic linear Geostatistics, (1998)
  • [2] Atteia O, Dubois J P, Webster R., Geostatistical analysis of soil contamination in the Swiss Jura, Environmental Pollution, 86, 3, pp. 315-327, (1994)
  • [3] Bi J W, Dong Q, Xue C J, Xu Y T., Extraction algorithm applied to northern Pacific mesoscale eddies based on altimetric remotely sensed data, Journal of Remote Sensing, 19, 6, pp. 935-946, (2015)
  • [4] Carr J R, Myers D E., Application of theory of regionalized variables to the spatoal analysis of Landsat data, IEEE Transactions on Geoscience and Remote Sensing, 22, pp. 55-61, (1984)
  • [5] Cecil C B, Tewalt S J., Coal extraction-environmental prediction, (2002)
  • [6] Chevrel S, Belocky R, Grosel K., Monitoring and assessing the environmental impact of mining in Europe using advanced Earth Observation Techniques-MINEO, Proceedings of the 16th Conference on Environmental Communication in the Information Society, pp. 519-526, (2002)
  • [7] Chevrel S, Kuosmannen V, Belocky R, Marsh S, Tukianiene T, Mollat H, Quental L, Vosen P, Schumacher V, Kuronen E, Aastrup P., Hyperspectral airborne imagery for mapping mining-related contaminated areas in various European environments-First results of the MINEO Project, 5th International Airborne Remote Sensing Conference, (2001)
  • [8] Clark I., Practical Geostatistics, (1981)
  • [9] David M J., Geostatistical Ore Reserve Estimation, (1977)
  • [10] Ellyett C D, Fleming A W., Thermal infrared imagery of the Burning Mountain coal fire, Remote Sensing of Environment, 3, 1, pp. 79-86, (1974)
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