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This study advances the understanding of land cover dynamics and socio-ecological transitions in Central African mining landscapes through a high-temporal-resolution analysis of the Luilu sector (southeastern DR Congo), a representative zone of the Katangese Copperbelt where mining, agriculture, and urbanization converge. By integrating ten Landsat epochs (1990–2024) with landscape-ecological indices within the Google Earth Engine environment, the research reconstructs three decades of spatial reorganization with multi-epoch analysis. The approach quantifies both the compositional and structural dimensions of Miombo woodland transformation using metrics of fragmentation, connectivity, and fractal complexity. Results reveal a pronounced contraction of forested areas (− 11.9%) and a parallel expansion of agricultural and urban surfaces, signifying the consolidation of an anthropogenic landscape matrix. Increasing spatial entropy and declining landscape stability indicate reduced structural resilience, while fractal patterns expose the disordered morphology typical of unregulated territorial growth. Methodologically, this framework enables the detection of short-term disturbance pulses and the structural quantification of landscape reorganization in heterogeneous tropical environments. Beyond the local scale, the approach provides quantitative foundations for sustainable land-use planning, restoration design, and the preservation of ecological connectivity in Central Africa’s rapidly transforming socio-ecological systems.
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Bwandamuka et al. (2026) studied this question.