Gold mining's environmental footprints, drivers, and future predictions in Ghana

Jacob Obodai, Shonil Bhagwat, Giles Mohan

Research output: Contribution to journalArticle (journal)peer-review

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Abstract

The last two decades have seen a surge in gold mining operations around the world. Despite mining occupying a smaller geographical area compared to other land use/land cover (LULC) classes, it exhibits strong interconnections with various land uses and serves as a major driver for changes in mining landscapes. Understanding and evaluating historical and potential future LULC changes in these landscapes are crucial in assessing the environmental impact of mining. Traditionally, these assessments heavily rely on geospatial techniques, with limited emphasis on projecting future LULC trends. This research aims to monitor, analyse the drivers of change, and predict future changes in LULC under two scenarios: the “business as usual” scenario and the "remedial measures" scenarios. Utilising the CA-Markov model, this article predicts LULC changes and offers comprehensive insights into the environmental impacts of mining, combining geospatial and social research methodologies. The investigation spanned a 34-year period (1986–2020) and employed a blend of supervised and unsupervised image classification methods, complemented by interviews, focus groups, and field observations. The findings reveal substantial land degradation, water pollution, and a significant loss of forest cover, accounting for 27,333 ha (36%). Continuation of current mining practices is predicted to lead to further ecological deterioration.
Original languageEnglish
Article number101103
Pages (from-to)1-17
Number of pages17
JournalRemote Sensing Applications: Society and Environment
Volume33
Early online date24 Nov 2023
DOIs
Publication statusPublished - 2 Dec 2023

Keywords

  • Land use land cover change
  • Ecological footprint
  • Remote sensing/GIS
  • CA-Markov
  • Mining
  • Prediction
  • Social sciences techniques

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