Construction of landscape eco-geological risk assessment framework in coal mining area using multi-source remote sensing data.

High-intensity and large-scale mining activities have aggravated regional eco-geological risk. Therefore, it is significantly essential to conduct an assessment of the eco-geological risk of mining areas. Although some progress has been achieved in ecological risk assessment studies, existing approaches are not entirely suitable for coal bases with high landscape fragmentation and dense coal mining activities. Here, we developed a novel landscape ecological and geological risk (LEGR) assessment framework based on theories that include landscape ecological risk and eco-geological risk. The framework selected 10 indicators, including slope, fluctuation, lithological hardness, soil type, FVC, RSEI, precipitation, biological abundance, distance to road and subsidence rate, and calculated the weights of indicators by introducing the AHP-CRITIC coupled weighting model. Then, the impact of landscape disturbances on eco-geological risk is quantified by measuring landscape losses. This framework was applied to the Shenfu mining area (SFMA), a typical coal base in northwest China. The results indicated the LEGR was moderate in the SFMA whose spatial distribution exhibited an increasing trend from southwest to northeast. Besides, the high LEGR was mainly in the aggregated mining area with high subsidence. For the eco-geological environment monitoring at the mine scale, a multiscale geographically weighted regression (MGWR) model was utilized for analyzing the relationship between indicators and LEGR within the disturbed range of coal mining. It provided valuable insights for the formulation of environmental protection policies in the mining area. • A novel landscape ecological geological risk (LEGRI) model was constructed. • The spatial characteristics of landscape ecological geological risk were analyzed. • The multiscale geographically weighted regression (MGWR) model was used to design eco-geological risk monitoring scheme at mining area scale. • The subsidence rate was calculated by SBAS-InSAR technology and used as an index of geological conditions. [ABSTRACT FROM AUTHOR]