Monitoring Mining Disturbance and Restoration over RBM Site in South Africa Using LandTrendr Algorithm and Landsat Data

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dc.contributor.authorDlamini, Lubanzi Z. D.
dc.contributor.authorXulu, Sifiso
dc.date.accessioned2020-01-27T07:53:26Z
dc.date.available2020-01-27T07:53:26Z
dc.date.issued2019
dc.descriptionPeer reviewed article published under Journals Sustainability Volume 11 Issue 24en_US
dc.description.abstractConsidering the negative impact of mining on ecosystems in mining areas, the South African government legislated the Mineral and Petroleum Resources Development Act (No. 28 of 2002), to compel mining companies to restore the land affected by mining. Several studies have used remotely sensed data to observe the status and dynamics of surface mines. Advances in remote sensing along the cloud-based Google Earth Engine (GEE) now promise an enhanced observation strategy for improved monitoring of mine environments. Despite these advances, land rehabilitation at Richards Bay Minerals (RBM) is mainly restricted to field-based approaches which are unable to reveal seamless patterns of disturbance and restoration. Here, we illustrate the value of the trajectory-based LandTrendr algorithm in conjunction with GEE for mine rehabilitation studies. Our automated method produced disturbance and recovery patterns (1984–2018) over the RBM site. The study revealed that RBM has progressively been mining different portions of the mineral-rich coastal area after which restoration was undertaken. The duration of mining over each site ranged from 2 to 6 years. The LandTrendr outputs correspond with independent reference datasets that were classified with an overall accuracy of 99%; it captures mine-induced disturbance efficiently and offers a practical tool for mine restoration management.en_US
dc.identifier.citationDlamini, L.Z. and Xulu, S., 2019. Monitoring Mining Disturbance and Restoration over RBM Site in South Africa Using LandTrendr Algorithm and Landsat Data. Sustainability, 11(24), p.6916.en_US
dc.identifier.issn2071-1050
dc.identifier.urihttps://doi.org/10.3390/su11246916
dc.identifier.urihttps://hdl.handle.net/10530/1987
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectrestorationen_US
dc.subjectminingen_US
dc.subjectLandsaten_US
dc.subjectGoogle Earth Engineen_US
dc.subjectcoastal dune foresten_US
dc.subjectRichards Bay Mineralsen_US
dc.subjectKwaZulu-Natal; South Africaen_US
dc.titleMonitoring Mining Disturbance and Restoration over RBM Site in South Africa Using LandTrendr Algorithm and Landsat Dataen_US
dc.typeArticleen_US
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