The research team, led by Samkelisiwe Khanyile, combined post-classification change detection in a geographic information system with chi-square statistical testing and a spatial clustering index. Their raw material was the South African National Land Cover dataset, built from Landsat 5 Thematic Mapper imagery for 1990 and Landsat 8 Operational Land Imager imagery for 2020, both at a 30-meter resolution. The original 73 and 72 land cover classes were collapsed into 12 comparable categories, allowing every one of nearly 2.9 million pixels to be traced from its 1990 state to its 2020 state. The resulting transition matrix, a 12-by-12 table of conversions, became the evidentiary backbone for asking whether landscape change in a post-mining region follows logic, chance, or policy failure.

The statistical verdict was unambiguous. The chi-square test returned a value of 11,319,251.69 with 121 degrees of freedom and a p-value below 0.001, and 141 of the 144 possible transitions proved significant. Cramér’s V, a measure of effect size, reached 0.60, indicating that the transitions substantially reshaped the composition of the landscape rather than nudging it at the margins. In plain terms, the land did not drift randomly into new uses. Institutional, economic, and planning forces drove the conversions, which means the inequities embedded in those conversions are also the product of decisions, not accidents.

The headline numbers tell a story of paradox. On one hand, 54.53 square kilometers of former mining land, 37.8 percent of the mining footprint recorded in 1990, successfully transitioned to natural vegetation, a conversion that occurred far more often than chance would predict and that points to genuine revegetation efforts. On the other hand, the wider landscape degraded. Natural vegetation shrank by 150.33 square kilometers, planted vegetation plummeted by 47.6 percent, waterbodies and wetlands declined by more than 12 percent, and barren land surged by 376.4 percent. Site-level rehabilitation, in other words, could not counteract landscape-scale ecological loss, a finding that echoes international evidence that point-source restoration rarely offsets cumulative regional damage.

Urbanization compounded the pressure. Built-up formal areas grew by 60.74 square kilometers, commercial areas nearly doubled with a 37.41 square kilometer expansion, and informal settlements exploded by 42.91 square kilometers, an astonishing 847.89 percent increase. Informal settlements also showed a persistence rate of only 45.42 percent, meaning they are constantly forming, dissolving, and reforming. Crucially, the spatial clustering index derived from the chi-square residuals reached 99,240.66, far above the 1,000-to-5,000 range expected from random distributions. The changes concentrated in Soweto, Tsakane, Simunye, Daveyton, and Mohlakeng, townships historically designated for Black residents under apartheid and deliberately sited near mining operations.

That geographic concentration is where the study’s environmental justice argument becomes sharpest. Environmental justice scholarship has long held that hazards are disproportionately placed near marginalized populations, but demonstrating this with quantitative landscape evidence has been rare in mineralized urban contexts of the Global South. Here, three lines of evidence converge: the transitions are systematic, they cluster in previously disadvantaged areas, and they include residential development on contaminated land. The belt hosts more than 270 tailings storage facilities covering roughly 400 square kilometers, some of them radioactive because of uranium co-occurring with gold. Provincial authorities identified 157 of 374 mine residue sites as radioactive, spanning 220 square kilometers.

Perhaps the most damning finding concerns the buffer zones that were supposed to keep people away from that contamination. In 2003, the Gauteng Department of Agriculture and Rural Development established pollution buffers around mine residue sites, later codified at distances of 500 to 1,500 meters under the 2012 Gauteng Pollution Buffers Policy, amended in 2017. Yet the analysis found that 0.80 square kilometers of mining land was converted to formal and informal built-up areas, placing residents directly adjacent to potentially contaminated ground despite explicit regulatory protection. The study also documents the reverse flow: 41.55 square kilometers of natural vegetation was converted to mining-related land use, showing that extraction continued consuming green space even as the sector contracted overall, with mining land declining only marginally from 144.25 to 143.28 square kilometers.

The authors frame this as a policy-implementation gap with two possible readings, both unjust. Either mining companies successfully defended their land holdings through regulatory power, monopolizing urban land while housing-poor populations are pushed onto the highest-risk zones, or mining actors strategically permitted settlement in buffer zones to monetize their land assets. Either way, the injustice is both spatial and temporal: apartheid-era mining footprints continue to structure environmental exposure and development opportunity three decades after the regulatory regime that produced them was formally dismantled. South Africa’s post-apartheid legal architecture, including the Constitution’s environmental rights clause, the National Environmental Management Act, the Mineral and Petroleum Resources Development Act with its mandatory rehabilitation provisions, and the Spatial Planning and Land Use Management Act, has not translated into protection on the ground.

The sustainability implications reach beyond South Africa. The findings show direct misalignment with Sustainable Development Goal 11 on sustainable cities, since urban growth in the mining belt has been predominantly informal and hazard-adjacent rather than planned, and with SDG 15 on terrestrial ecosystems, given the vegetation losses and barren land expansion. Gauteng’s position on a watershed divide between the Crocodile, Olifants, and Vaal river systems makes the wetland losses particularly troubling, as the landscape loses its capacity to retain and filter water precisely when demand is escalating. Acid mine drainage, soil contamination, and radioactive dust remain persistent threats that satellite imagery cannot capture, which the authors acknowledge as a limitation alongside their reliance on two time points and pre-classified 30-meter data with 88 to 96 percent accuracy.

What distinguishes this study is its replicable methodological template: transition matrices validated by chi-square testing, effect sizes, and clustering indices, all benchmarked against regulatory buffer zones. Because the changes are systematic, the authors argue, they can be deliberately reversed through targeted intervention. Their prescriptions include stronger regulatory enforcement with meaningful penalties, affordable housing provision to relieve pressure on contaminated land, participatory rehabilitation planning that centers community voices, and accountability mechanisms grounded in independently verifiable landscape-scale evidence rather than self-reported site compliance. A periodic land cover monitoring framework benchmarked against the provincial buffer policy could, they suggest, turn satellite pixels into enforceable metrics. The Witwatersrand’s golden scar will not heal on its own, but for the first time its growth, its healing patches, and its human costs have been measured with a precision that regulators can no longer ignore.

Subject of Research: Mining-driven land use and land cover change and environmental justice along the Witwatersrand mining belt, Gauteng, South Africa, 1990–2020

Article Title: Mining Legacies and Environmental Injustice: Systematic Mining-Led LULC Change in the Witwatersrand Mining Belt, Gauteng, South Africa (1990–2020)

Article References: Khanyile, S., Tsoriyo, W., & Mahamuza, P. (2026). Mining Legacies and Environmental Injustice: Systematic Mining-Led LULC Change in the Witwatersrand Mining Belt, Gauteng, South Africa (1990–2020). Environmental Management, 76(10), Article 336. https://doi.org/10.1007/s00267-026-02543-9

Image Credits: AI Generated

DOI: 10.1007/s00267-026-02543-9

Keywords: land use land cover change, mining, environmental justice, Witwatersrand, Gauteng, remote sensing, GIS, chi-square analysis, informal settlements, mine rehabilitation, tailings storage facilities, sustainable development goals