Monitoring the effects of open-pit mining on the eco-environment using a moving window-based remote sensing ecological index

Environ Sci Pollut Res Int. 2020 May;27(13):15716-15728. doi: 10.1007/s11356-020-08054-2. Epub 2020 Feb 21.

Abstract

Environmental problems caused by mines have been increasing. As one of the most serious types of mining damage caused to the eco-environment, open pits have been the focus of monitoring and management. Previous studies have obtained effective results when evaluating the ecological quality of a mining area by using the remote sensing ecological index (RSEI). However, the calculation of RSEI does not consider that the ecological environmental impact is limited under natural conditions. To overcome this shortcoming, this paper proposes an improved RSEI based on a moving window model, namely the moving window-based remote sensing ecological index (MW-RSEI). This improved index is more in agreement with the First Law of Geography than RSEI. This study uses Landsat ETM/OLI/TIRS images to extract MW-RSEI information of a case area in Zhengzhou City, Henan Province, central China, in 2009 and 2018. The results revealed that the average value of MW-RSEI declined from 0.668 to 0.611 from 2009 to 2018, and the main drivers of the deterioration of the eco-environment were land use/cover (LUCC) changes, most of which were derived from urban expansion and mining. The serious impact of open pits on the eco-environment in mining areas is mainly due to their low vegetation cover; therefore, some effectively managed open pits can have a positive impact on the mining environment. The use of MW-RSEI provides valuable information on the eco-environment surrounding the open pit, which can be used for the rapid and effective monitoring of the eco-environment in mining areas.

Keywords: Eco-environment monitoring; Moving window; Open-pit mining; Remote sensing; Remote sensing ecological index (RSEI).

MeSH terms

  • China
  • Cities
  • Conservation of Natural Resources
  • Ecosystem*
  • Environmental Monitoring
  • Mining
  • Remote Sensing Technology*