Samkelisiwe Khanyile

: Mining activities significantly shape landscapes and often pose sustainability and environmental justice challenges for surrounding communities. This paper examines land use and land cover (LULC) transitions and their sustainable development implications along the Witwatersrand mining belt in Gauteng, South Africa (1990–2020). Leveraging geospatial analysis, chi-square statistical testing, and spatial clustering, the findings highlight a critical tension between mining and sustainability efforts. While 54.53 km² of mining areas successfully transitioned to natural vegetation, landscape-scale degradation persisted, natural and planted vegetation declined, and barren land increased, with informal settlements also increasing and concentrating in mining-adjacent areas. Statistical significance tests (χ² = 11,319,251.69, p < 0.001; Cramér’s V = 0.60) indicate that 97.9% of transitions are systematic rather than random, and that they concentrate in previously disadvantaged communities. Mining land was also converted to residential areas despite regulatory protections and buffer zones, indicating a policy and implementation gap. This study highlights the crucial role of LULC assessments in post-mining landscape management, concluding that practical mining sustainability requires an integrated approach of stronger regulation, affordable housing, participatory rehabilitation planning, and accountability mechanisms grounded in quantitative evidence of distributive and environmental justice.

Post-mining landscapes are multifaceted, comprising multiple characteristics, more so in big metropolitan regions such as Gauteng, South Africa. This paper evaluates the efficacy of Fuzzy overlay and Random Forest classification for integrating and representing post-mining landscapes and how this influences the perception of these landscapes. To this end, this paper uses GISs, MCDA, Fuzzy overlay, and Random Forest classification models to integrate post-mining landscape characteristics derived from the literature. It assesses the results using an accuracy assessment, area statistics, and correlation analysis. The findings from this study indicate that both Fuzzy overlay and Random Forest classification are applicable for integrating multiple landscape characteristics at varying degrees. The resultant maps show some similarity in highlighting mine waste cutting across the province. However, the Fuzzy overlay map has higher accuracy and extends over a larger footprint owing to the model’s use of a range of 0 to 1. This shows both areas of low and high memberships, as well as partial membership as intermediate values. This model also demonstrates strong relationships with regions characterised by landscape transformation and waste and weak relationships with areas of economic decline and inaccessibility. In contrast, the Random Forrest classification model, though also useful for classification purposes, presents a lower accuracy score and smaller footprint. Moreover, it uses discrete values and does not highlight some areas of interaction between landscape characteristics. The Fuzzy overlay model was found to be more favourable for integrating post-mining landscape characteristics in this study as it captures the nuances in the composition of this landscape. These findings highlight the importance of mapping methods such as Fuzzy overlay for an integrated representation and shaping the perception and understanding of the locality and extent of complex landscapes such as post-mining landscapes. Methods such as Fuzzy overlay can support research, planning, and decision-making by providing a nuanced representation of how multiple landscape characteristics are integrated and interact in space and how this influences public perception and policy outcomes.

In the last 30 years of democracy, the focus has been on delivering basic services to households. Yet there are larger infrastructure challenges faced at a local level, including rising dissatisfaction regarding the quality of services delivered. Insights generated from ongoing discussions on Gauteng's energy and water landscape indicate that, central to the service delivery discourse, delivering services goes beyond mere physical access. Using household survey data for Gauteng, we show it is necessary to make services more affordable and reliable, emphasising the need for innovation, inclusion, and placing equitable distribution at the core of infrastructural and service delivery planning.