Sustainable and responsible mining through sound mine closure

Chugh, Yoginder P.; Schladweiler, Brenda K.; Skilbred, Chet

doi:10.1007/s40789-023-00572-x

Cited by 7 publications

(3 citation statements)

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“…Rather, it is the beginning of post-mining reclamation and rehabilitation, which is the responsibility of the mining company. Post-mining reclamation aims to restore the mined-out areas to their initial state before mining [21] or to a comparable alternative that provides ecological and social benefits. In most cases, post-mining reclamation is planned based on the initial setting before mining, such as a forest [22], and involves the restoration of soil, water, and vegetation.…”

Section: Contextual Framework 21 Post-mining Managementmentioning

confidence: 99%

Building a Community’s Adaptive Capacity for Post-Mining Plans Based on Important Performance Analysis: Case Study from Indonesia

Sutrisno

Chen

Suryawan

et al. 2023

Land

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Preparing communities around mines to face the impacts of mine closures is crucial in order to reduce disruptions to their livelihoods. Building the adaptive capacity of these communities will alleviate the burden on governments or mining companies in the future. Unfortunately, adaptive capacity has not yet been integrated into post-mining planning policies. This research aims to develop an adaptive capacity framework for post-mining planning in local communities, focusing on a case study conducted in Indonesia. We developed this framework using the Importance Performance Analysis (IPA) method. The findings indicate that the adaptive capacity framework provides a comprehensive approach to building the capacity to adapt and thrive in post-mining situations. This highlights the importance of continuing to disseminate post-mining plan information, prioritizing access to capital and former mine sites, fostering collaboration, and creating job opportunities. Simultaneously, efforts to increase skills should be reduced, and reallocation of efforts towards community institution building, establishing information centers, and improving community bonds should be prioritized in more important fields and programs. By adopting this framework, communities around mines in Indonesia are expected to enhance their resilience and ability to effectively respond to changing circumstances.

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Section: Contextual Framework 21 Post-mining Managementmentioning

confidence: 99%

Building a Community’s Adaptive Capacity for Post-Mining Plans Based on Important Performance Analysis: Case Study from Indonesia

Sutrisno

Chen

Suryawan

et al. 2023

Land

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“…Intense levels of human activity, such as mining, have caused extensive vegetation removal or degradation in many areas [1,2]. In recent years, important ecological restoration efforts have gained popularity; for instance, the United Nations recently declared 2021-2030 as the decade for ecosystem restoration [3].…”

Section: Introductionmentioning

confidence: 99%

Mapping Foliar C, N, and P Concentrations in An Ecological Restoration Area with Mixed Plant Communities Based on LiDAR and Hyperspectral Data

Yang,

Dong,

Tang

et al. 2024

Remote Sensing

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Interactions between carbon (C), nitrogen (N), and phosphorus (P), the vital indicators of ecological restoration, play an important role in signaling the health of ecosystems. Rapidly and accurately mapping foliar C, N, and P is essential for interpreting community structure, nutrient limitation, and primary production during ecosystem recovery. However, research on how to rapidly map C, N, and P in restored areas with mixed plant communities is limited. This study employed laser imaging, detection, and ranging (LiDAR) and hyperspectral data to extract spectral, textural, and height features of vegetation as well as vegetation indices and structural parameters. Causal band, multiple linear regression, and random forest models were developed and tested in a restored area in northern China. Important parameters were identified including (1), for C, red-edge bands, canopy height, and vegetation structure; for N, textural features, height percentile of 40–95%, and vegetation structure; for P, spectral features, height percentile of 80%, and 1 m foliage height diversity. (2) R2 was used to compare the accuracy of the three models as follows: R2 values for C were 0.07, 0.42, and 0.56, for N they were 0.20, 0.48, and 0.53, and for P they were 0.32, 0.39, and 0.44; the random forest model demonstrated the highest accuracy. (3) The accuracy of the concentration estimates could be ranked as C > N > P. (4) The inclusion of LiDAR features significantly improved the accuracy of the C concentration estimation, with increases of 22.20% and 47.30% in the multiple linear regression and random forest models, respectively, although the inclusion of LiDAR features did not notably enhance the accuracy of the N and P concentration estimates. Therefore, LiDAR and hyperspectral data can be used to effectively map C, N, and P concentrations in a mixed plant community in a restored area, revealing their heterogeneity in terms of species and spatial distribution. Future efforts should involve the use of hyperspectral data with additional bands and a more detailed classification of plant communities. The application of this information will be useful for analyzing C, N, and P limitations, and for planning for the maintenance of restored plant communities.

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“…However, the absorption of fracturing fluid into coal seams may have adverse effects [13]. Mine disaster prevention and control, mine management, and ecological environment restoration are also vital research areas [14]. Underground mining can lead to surface subsidence to a certain extent [15].…”

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confidence: 99%