Soil Water Retention Properties as the Key Driver for Rehabilitation

Hattingh, Rob; Viljoen, Celeste

doi:10.36487/acg_repo/605_28

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…As a result of this Act, all mining companies are required to set aside financial provisions for the discharge of their rehabilitation obligations, which can be reimbursed on the issuance of a closure certificate by the state regulator [20]. However, the issuance of a closure certificate implies that the state incurs financial liability to rehabilitate the land [21], and the government is currently facing an estimated cost of ZAR 30 billion (USD 2 billion) for this task [20].…”

Section: Introductionmentioning

confidence: 99%

Multi-Year Mapping of Disturbance and Reclamation Patterns over Tronox’s Hillendale Mine, South Africa with DBEST and Google Earth Engine

Xulu

Phungula

Mbatha

et al. 2021

Land

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This study was devised to examine the pattern of disturbance and reclamation by Tronox, which instigated a closure process for its Hillendale mine site in South Africa, where they recovered zirconium- and titanium-bearing minerals from 2001 to 2013. Restoring mined-out areas is of great importance in South Africa, with its ominous record of almost 6000 abandoned mines since the 1860s. In 2002, the government enacted the Mineral and Petroleum Resources Development Act (No. 28 of 2002) to enforce extracting companies to restore mined-out areas before pursuing closure permits. Thus, the trajectory of the Hillendale mine remains unstudied despite advances in the satellite remote sensing technology that is widely used in this field. Here, we retrieved a collection of Landsat-derived normalized difference vegetation index (NDVI) within the Google Earth Engine and applied the Detecting Breakpoints and Estimating Segments in Trend (DBEST) algorithm to examine the progress of vegetation transformation over the Hillendale mine between 2001 and 2019. Our results showed key breakpoints in NDVI, a drop from 2001, reaching the lowest point in 2009–2011, with a marked recovery pattern after 2013 when the restoration program started. We also validated our results using a random forests strategy that separated vegetated and non-vegetated areas with an accuracy exceeding 78%. Overall, our findings are expected to encourage users to replicate this affordable application, particularly in emerging countries with similar cases.

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Section: Introductionmentioning

confidence: 99%