ZHU Dongyu, CHEN Tao, NIU Ruiqing, ZHEN Na. Analyzing the Ecological Environment of Mining Area by Using Moving Window Remote Sensing Ecological Index[J]. Geomatics and Information Science of Wuhan University, 2021, 46(3): 341-347. DOI: 10.13203/j.whugis20190122
Citation: ZHU Dongyu, CHEN Tao, NIU Ruiqing, ZHEN Na. Analyzing the Ecological Environment of Mining Area by Using Moving Window Remote Sensing Ecological Index[J]. Geomatics and Information Science of Wuhan University, 2021, 46(3): 341-347. DOI: 10.13203/j.whugis20190122

Analyzing the Ecological Environment of Mining Area by Using Moving Window Remote Sensing Ecological Index

  •   Objectives  Mine environmental problems are intensifying, and the environmental monitoring and evaluation of the mining area is an indispensable part of mine management. Previous researches have obtained effective results by evaluating the mining ecological environment through the remote sensing ecological index (RSEI). However, the calculation does not take into account that the environmental influence is regional under natural conditions of RSEI, and the geo-graphical location of the mining area has different effects on its surrounding ecological environment. The main purpose of this research is to propose a new remote sensing ecological index that is more in line with the ecological response mechanism based on the characteristics of the ecological environment of the mining area.
      Methods  Aiming at the complex research area of large area feature type, this paper presents an improved ecological index named moving window-based remote sensing ecological index (MW-RSEI) which based on RSEI and moving window evaluation unit. MW-RSEI divides the ecological environment into four influencing factors: Greenness, wetness, dryness and heat. Each pixel in the study area is taken as the research object, and the extended window of the pixel is taken as the calculation range of each factor. The experiment assigns weight to the center pixel of each window through principal component analysis.
      Results  The MW-RSEI and RSEI models were used to calculate in the study area, the results show that the mean value of MW-RSEI and RSEI in the study area were 0.522 and 0.459, the greenness and wetness had positive effect on the environment, and the dryness and heat had negative effects. Based on the MW-RSEI model, mine geomorphology destroys the regional ecological environment grade is worst and poor accounted for 85.40% of the overall area. MW-RSEI in line with the first law of geography. Its results are consistent with RSEI, and it shows more gradient information of the ecological environment around the mining area, which confirms the theory of dissipative structure in the ecological environment.
      Conclusions  MW-RSEI refines the local characteristics of the ecological environment, and it can provide an effective basis for ecological environment monitoring and evaluation in mining areas.
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