Emergency Monitoring of a Tailings Pond Leakage Accident Based on the GEE Platform

Hengqian Zhao, Zihan Yang, Hongwei Zhang, Jianwei Meng, Qian Jin and Shikang Ming
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Hengqian Zhao: State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
Zihan Yang: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Hongwei Zhang: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Jianwei Meng: Hebei Research Center for Geoanalysis, Baoding 071051, China
Qian Jin: Hebei Research Center for Geoanalysis, Baoding 071051, China
Shikang Ming: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Sustainability, 2022, vol. 14, issue 14, 1-12

Abstract: The utilization of mineral resources plays an important role in supporting and promoting economic development and social progress. As a necessary facility for the development and utilization of mineral resources, tailings ponds will cause a series of safety and environmental problems once accidents occur. Based on the Sentinel-2 images obtained from the GEE (Google Earth Engine) platform, this paper carried out emergency monitoring of the Yichun Luming Mining tailings pond leakage accident on 28 March 2020, through the spectral changes in monitoring points in the downstream rivers of the tailings pond, the changes in the images before and after the accident, and the analysis of long-time series various indexes. The results revealed that the pollution was quickly treated in a short time, and the river spectrum returned to normal on April 13. The pollution spread for approximately 300 km downstream to the Yijimi River and the Hulan River, and was finally intercepted at the Lanxi Old Bridge 67 km away from the Songhua River, so that more serious pollution was avoided. This accident had a direct impact on the surrounding six counties. The decrease in NDVI reflects that the accident has a certain degree of influence on the vegetation around the tailings pond, while the change in NDTI reflects that some remedial measures have been taken for the tailings pond after the accident. This study demonstrates the advantages of the GEE platform for the emergency monitoring of accidents, which can provide a reference for the emergency monitoring of similar accidents.

Keywords: Google Earth Engine (GEE); Sentinel-2; tailings pond; emergency monitoring (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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