XIAO Wu, CHEN Wenqi, HE Tingting, et al. Remote sensing monitoring and impact assessment of mining disturbance in mining area with high undergroundwater level[J]. Journal of China Coal Society, 2022, 47(2): 922-933.
Citation: XIAO Wu, CHEN Wenqi, HE Tingting, et al. Remote sensing monitoring and impact assessment of mining disturbance in mining area with high undergroundwater level[J]. Journal of China Coal Society, 2022, 47(2): 922-933.

Remote sensing monitoring and impact assessment of mining disturbance in mining area with high undergroundwater level

  • Coal mining leads to surface subsidence and waterlogging,which is the main feature of coal mining areas in eastern plains with high underground water levels. Long term detection of changes in the subsidence water body is helpful to quantitatively evaluate the comprehensive impact of coal mining on land,ecology,and community. In the absence of underground mining knowledge as a guide,how to identify and distinguish the mining subsidence water body from the natural water body and the excavated water body caused by other human activities,and quantify the boundary and extent of the mining subsidence effects are difficult to be monitored by remote sensing only. This study takes the Yanzhou coalfield in Shandong Province as the study area. Based on all time series Landsat images available since 1986,the authors have developed a spatiotemporal dynamic mapping method to detect the changes of subsidence water and land reclamation based on trajectory data under Google Earth Engine (GEE) platform using the CCDC (Continue Change Detection and Classification) algorithm. Three indices of VSDI (Visible and Shortwave Infrared Drought Index),LSWI (Land Surface Water Index),and SMMI (Soil moisture monitoring index) that reflect the soil moisture was inverted in the buffer zone of the subsidence water body using Sentinel 2 data respectively. According to the spatial variation law of soil moisture content,the authors measured the spatial distribution characteristics of soil moisture at different distances from the subsidence water area,further quantitatively analyzed the influence range and degree of mining disturbance. The results show that ① The annual spatial and temporal data of surface subsidence water and reclamation caused by underground coal mining from 1986 to 2017 were identified based on the CCDC algorithm with an accuracy of 85% and 77%,respectively. ② From 1990 to 2017,a waterlogged area of 3 021.08 hectares was accumulated in the study area,about 75.80% of which occurred from 2001 to 2011. Subsidence water reclamation occurred after 1993,with a cumulative area of 888.37 hectares,accounting for 29.41% of the total subsidence water area,mainly concentrated after 2007. ③ The impact of subsidence water is mainly concentrated within 120 m from the periphery of the subsided water body,where drastic soil moisture changes occur in this area. There is a disturbance within 120-300 m,but the influence intensity is slight. Almost there is no effect beyond 300 m. In this paper,the authors analyzed the long time series of subsidence water change in the mining area and identified the influence range and degree of mining disturbance based on the remote sensing inversion of soil moisture in the high phreatic level mining area. It provides a new method for monitoring,identification and impact assessment on mining subsidence water in the similar mining area.
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