Mapping the components and dynamics of surface coal mines using time-series Landsat imagery

Accurate and efficient monitoring of surface coal mines’ distribution and change dynamics is essential for sustainable land resource management. However, existing studies have mainly focused on disturbances to surrounding vegetation, with relatively little attention to internal components and their dynamic evolution. To provide a more comprehensive assessment of mining-induced land impacts, this study develops a novel approach for mapping the extent, components, and dynamics of surface coal mines using multi-decadal Landsat time-series imagery. A Global and Local Composite Threshold Segmentation (GLCTS) is proposed to delineate mining extent, followed by a Multiple Hierarchical Index-based Classification (MHIC) to extract internal components. The relationship between extent changes and component succession is further revealed across the mining life cycle. Applied to three major energy-producing provinces in northern China, the method achieves an overall accuracy exceeding 90%. The results show that the accumulated destruction area reached 3811.09 km2, while reclamation covered 2628.55 km2 over the past four decades, with waste rock identified as the dominant component (58.47%). The findings reveal that internal components follow a regular pattern of succession during the mining process, uncovering the heterogeneous and dynamic characteristics of mining interiors and offering new insights into their spatiotemporal processes and life-cycle evolution.