TY - JOUR
T1 - Gold mining's environmental footprints, drivers, and future predictions in Ghana
AU - Obodai, Jacob
AU - Bhagwat, Shonil
AU - Mohan, Giles
PY - 2023/12/2
Y1 - 2023/12/2
N2 - 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.
AB - 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.
KW - Land use land cover change
KW - Ecological footprint
KW - Remote sensing/GIS
KW - CA-Markov
KW - Mining
KW - Prediction
KW - Social sciences techniques
UR - https://doi.org/10.1016/j.rsase.2023.101103
UR - http://www.scopus.com/inward/record.url?scp=85179116318&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85179116318&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/98f1e906-3aea-3119-88bd-994f2bb28abc/
U2 - 10.1016/j.rsase.2023.101103
DO - 10.1016/j.rsase.2023.101103
M3 - Article (journal)
SN - 2352-9385
VL - 33
SP - 1
EP - 17
JO - Remote Sensing Applications: Society and Environment
JF - Remote Sensing Applications: Society and Environment
M1 - 101103
ER -