0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free Access<p>Rare earth elements (REE) mines have an extremely high strategic value, especially, in national aerospace industry and military fields. The long-term open mining and extraction processing of REE in the weathered crust since 1970s have led to serious land degradation, e.g., vegetation degradation, soil loss, reduction of soil fertility, and especially, environmental pollution to subsoil and groundwater. Taking southern Jiangxi, where ion-type of REE mines are mainly located, as an instance, the total mining area is measured about 79 km<sup>2</sup> from 1291 mines, of which 56 km<sup>2</sup>  have been or are being managed with restoration measures identified by comparison between multitemporal very high resolution images available on Google Earth. Visual interpretation revealed that large-scale mining activities occurred after 2000 and restoration management was not intervened until 2010, in particular, 2013. As implemented by different enterprises or companies, post-mining restoration has a strong spatial variability in both management approaches and effectiveness from mine to mine. Up to today, no systematic monitoring and assessment have been conducted for this restoration intervention. It is, therefore, the objective of our study to evaluate the effectiveness of such restoration efforts using multitemporal October Landsat data with scene path/row number of 121/42-121/43 from 2000 to 2017. Eight managed and seven unmanaged typical mines were selected for a comparative analysis and restoration assessment.</p><p>After atmospheric correction using COST model, NDVI and GDVI (Generalized Difference Vegetation Index) that is more suitable for low vegetation, as proxy of vegetation vigor and biomass production, were derived from all satellites images. The mean NDVI and GDVI values of each selected mine were calculated. The results show that NDVI of the managed REE mines has been increasing from 0.32 to 0.67 and GDVI from 0.55 to 0.90 year by year since 2010, indicating a vegetation recovery, especially, for those with effective management. In contrast, in the unmanaged mines, NDVI values remain low ranging from 0.20 to 0.40, and GDVI from 0.22 to 0.60, implying that the damaged vegetation cover caused by open mining and pollution has low capacity to recover without human intervention, where continue serious water loss and soil erosion. We also noted in some managed areas that planted grasses have survived but trees died or are dying probably because of the residual pollution in subsoil. This means a holistic management should be implemented in both surface, subsoil and groundwater, and monitoring be conducted by remote sensing in combination with soil sampling. This will be our next task of research.</p><p> </p>
Lifeng Xie, Weicheng Wu, Xiaolan Huang, Penghui Ou, Ziyu Lin, Yingwei Song, Zhong Lin Wang, Tao Lang, Wenchao Huangfu, Yang Zhang, Zhou Xiao-ting, Xiao Fu, Jie Li, Jingheng Jiang, Ming Zhang, Zhenjiang Zhang, Yaozu Qin, Shanling Peng, Chongjian Shao (2020). Restoration monitoring of rare earth element (REE) mines in southern Jiangxi, China. , DOI: https://doi.org/10.5194/egusphere-egu2020-8255.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2020
Authors
19
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.5194/egusphere-egu2020-8255
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access
