Environ Monit Assess. 2026 Aug 15;198(9):951. doi: 10.1007/s10661-026-15801-4.
ABSTRACT
Open-cast coal mining can alter land cover rapidly, yet annual assessments may overlook the episodic nature of disturbance and partial vegetation recovery. This study examined decadal land-cover dynamics within the Northern Coalfields Limited operational landscape of the Singrauli-Sonbhadra coal belt, India, from 2016 to 2025. Temporally consistent January Landsat 8-9 Collection 2 Level-2 Surface Reflectance imagery was classified into four NDVI-based land-cover classes: barren/mining, sparse vegetation, moderate vegetation, and dense vegetation. Annual class distributions were evaluated using the Mann-Kendall test and Sen’s slope estimator, while a pixel-based 2016-2025 transition matrix quantified gross endpoint transitions. SRTM-derived slope data provided additional topographic context. Across the common mapped domain of approximately 322.17 km2, the barren/mining class increased from 114.28 km2 in 2016 to 158.05 km2 in 2025, equivalent to an increase of 43.77 km2 or 13.59 percentage points of landscape coverage. None of the four classes showed a statistically significant monotonic trend (p > 0.05). The largest off-diagonal endpoint transition was from sparse vegetation to barren/mining land (59.80 km2), compared with 16.20 km2 in the reverse direction. Slope analysis showed systematic differences in the terrain distribution of land-cover classes, although the largest absolute barren/mining extent occurred on near-level ground. The findings demonstrate the value of combining annual NDVI mapping, non-parametric trend analysis, transition matrices, and terrain context for long-term monitoring of mining-affected landscapes.
PMID:42603206 | DOI:10.1007/s10661-026-15801-4
