321 / 2023-10-14 19:07:27

A remote sensing index for assessing long-term ecological impact in arid mined land 

Arid area; Open-pit mining; Mined land ecological status index; Spatial-temporal change; Ecological status

The satellite remote sensing technology has advantage to record land surface condition of spatial and temporal coverage, which has been widely and effectively used in assessing mine environment. The western China with semi-arid ecosystems, as the most important mineral resources area, have at least ten super-large mineral bases including coal, non-ferrous metal ores, metal mine, etc. The surface mining activities, which is characterized by large spatial and temporal scales, would accelerate the fragility and changes to the ecological environment in the vulnerable areas. Therefore, in terms of the green mine construction and mine reclamation, it is of great significance to evaluate and understand the mining impacts spatially and temporally in the arid ecological systems. This paper selected three typical open-pit mines in arid areas of Xinjiang, China as the research area (site Ⅰ: Jinbao Iron open-pit mine, site Ⅱ: Heishan coal open-pit mine, site Ⅲ: Wulagen Lead Zink open-pit mine). The main objective of this study was to develop a remote sensing index (mined land ecological status index, MLESI) by considering the biological factors of dryness, bare soil flatness, land surface temperature and slope for assessing ecological status in mining area of arid land. Afterwards, Principal Component Analysis was used to coupling four factors for constructing MLESI. Moreover, the ability of MLESI was compared with remote sensing ecological index (RSEI) and Land Surface Ecological Status Composition Index (LSESCI) under different landform in arid mining area characterized with bare soil and rock. Finally, the spatial and temporal change of mining effect from 2005 to 2020 was analyzed based on Landsat time series images by using the Sen+Mann-Kendall method. The results showed that (1) The average Pearson correlation coefficient (r) between MLESI and each factor was over 0.65. The factor of heat had highest correlation coefficient of 0.8 with MLESI for mine site Ⅰ. For mine site Ⅱ, the factor of dryness correlated with MLESI with highest value of 0.82. And the factor of slope had highest correlation coefficient of 0.82 for mine site Ⅲ. (2) For mine site Ⅰ and Ⅱ, the area of ecological status with poor level were overestimated by LSESCI, which identified the most of natural land as poor level. RSEI was not able to reveal the ecological status change correlating with landform variety. In general, MLESI was not only highly capable of characterizing the mining area from natural bare soil and rock from lands, but could indicate ecological changes along mining direction with landform changing. (3) The ecological status in mine site I degraded by the rate of 54.84% since 2015 with large surface mining activities. For mine site II, the ecological status gradually decreased from MLESI value of 0.68 in 2005 to 0.38 in 2020. In total of 2.36 km² area has significantly change with poor ecological status during 15 years. For mine site Ⅲ, the ecological status was improved by land reclamation, which showed the highest MLESI value of 0.77 at 2017. The area of 0.95 km² had a significantly change with good ecological status from 2008 to 2020. Thus, the proposed MLESI outperformed RSEI and LSEISCI in different mine ecological status monitoring in typical arid ecosystem.