article · Discover Forests
Analysis of the Luilu mining sector in the Democratic Republic of the Congo reveals significant land cover changes between 1990 and 2024. Using satellite observations across ten intervals alongside landscape-ecological metrics, the evaluation tracks the transformation of Miombo woodlands amidst expanding mining, agriculture, and urbanisation. Over this thirty-four-year timeframe, forested areas contracted by 11.9 percent, while farming and built environments expanded to form a predominantly human-modified landscape. Measurements of fragmentation, connectivity, and fractal patterns demonstrate rising spatial disorder, declining stability, and weakened structural resilience across the ecosystem. This analytical method detects short-term ecological disturbance pulses and quantifies physical landscape reorganisation. The findings establish quantitative data to support future land-use planning, ecological restoration, and the maintenance of habitat connectivity in rapidly developing mining regions across Central Africa.
Rapid expansion of mining and urban centres across Central Africa exerts immense pressure on native woodlands. By tracking three decades of habitat loss and structural fragmentation, these findings expose how unregulated growth weakens ecological resilience. This information is critical for environmental managers and policymakers seeking to balance vital mineral extraction with land conservation and sustainable regional development.
The framework offers an applied tool for land-use planners, mining operators, and conservation agencies requiring quantitative environmental monitoring. By utilising satellite imagery to assess ecological degradation and fragmentation, the system can support environmental impact assessments and post-mining restoration design. The methodology represents applied analytical research that could be integrated into spatial planning software or commercial environmental compliance services for extractive industries operating across Central Africa.
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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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DOI: 10.1007/s44415-026-00117-5
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