| Popis: |
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. |
