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Remote sensing studies plotted on the ecological recovery wheel for monitoring projects (International Society for Ecological Restoration (SER)) based on their primary objective and rescaled by the sub-attribute spatial mosaic which had the highest number of studies at 59 (A). Potential application of remote sensing opportunities for monitoring in mine site rehabilitation (B). This figure was adapted from the ecological recovery wheel, accessed at http://seraustralasia.com/wheel/wheel.html.
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The mining industry has been operating across the globe for millennia, but it is only in the last 50 years that remote sensing technology has enabled the visualization, mapping and assessment of mining impacts and landscape recovery. Our review of published literature (1970–2019) found that the number of ecologically focused remote sensing studies...
Contexts in source publication
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... the temporal scale, the studies were mostly uni-temporal (36%) or decadal (23%), and the classification methods tended to focus on supervised (43%) or manual methods (33%) ( Figure 2D,E). Figure 3A shows the SER ecological recovery wheel categorized for the 93 research papers. (Note that of the total 99 papers, 4 review papers and 2 DSS were omitted from this assessment). ...
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... total number of papers for each category were rescaled, based on the maximum number of studies for a single sub-attribute, which was 59 (63%) for the sub-attribute spatial mosaic. As a result, all other sub-attributes were rescaled to 1 or below on the ecological recovery wheel scale ( Figure 3A). This demonstrated that the literature was dominated by LULC studies, while a smaller proportion focused on ecosystem function (productivity/cycling) (11%) or external exchanges/landscape flows (7%). ...
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... is our opinion that remote sensing has the potential to address 16 of 18 sub-attributes in the ecological recovery wheel, as shown in Figure 3B. Twelve sub-attributes scored a maximum of 5, suggesting that remote sensing is capable of assessing metrics including resilience/recruitment, invasive species, desirable plants, and all vegetation strata. ...
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... animals scored 3 indicating a moderate capacity for assessment. All three physical conditions sub-attributes scored 2, suggesting a low capacity, while gene flows and all trophic levels scored zero, suggesting remote sensing is not suitable ( Figure 3B). Figure 4 shows the frequency of spectral indices used as a total of the reviewed publications. ...
Citations
... Each index has its advantages and limitations, and NDVI is no exception; however, its efficacy has been reported to be on par with (Huete et al., 1997;Mróz & Sobieraj, 2004) or better (Kariyawasam et al., 2014;Purevdorj et al., 1998) than some of the other indices (Saini et al., 2019). NDVI has been reported to be the most commonly used index for studying mine site rehabilitation for ecological outcomes (McKenna et al., 2020). ...
The widespread usage of coal for power generation necessitates continuing mining. While producing a valuable resource, this method significantly degrades the natural environment, notably the local vegetation. Once mining has stopped, reclaiming the destroyed areas to restore the natural landscape is critical. Mining activities have been going on for centuries; however, monitoring reclaimed areas through field-based methods is inefficient and time-consuming. In contrast, the expanding accessibility of geospatial data over the last five decades has aided in the accurate and consistent mapping and monitoring of reclaimed mining zones. Keeping in line, the present study utilized Landsat TM/OLI data from 2005 to 2021 to track reclamation success in a part of Jharia Coalfield, India. The methods included deriving Normalized Difference Vegetation Index (NDVI) images to evaluate the spatiotemporal variation of vegetation health, density, and vigour; and visual appreciation using a variety of RGB combinations of three date NDVI images. Later, a statistical threshold method based on Z-scores was employed to quantify the NDVI change values into three categories- Decrease, Unchanged and Increase. According to these analyses, the reclamation success in the study area ranged from modest to good. In the two focus areas, there has been an increase of 72 and 76 hectares in the Increase class. The accuracy of the classified change image was calculated to be 84.4 per cent. Until recently, no such work has been reported from the study area. The present research results are critical to mining professionals, environmentalists, and society and provide a promising way to inform about the success of reclamation activities and their monitoring.
... Nowadays, based on the importance of mine ecological environment, it is very necessary to carry out ecological restoration of abandoned mines, and at the same time of ecological restoration, the restoration benefit is also an important index for evaluating the reasonableness of restoration methods, and on the basis of the evaluation indexes, it is possible to analyze the problems of the existing restoration methods, so as to realize the further optimization of restoration methods [13][14][15]. The ecological restoration benefit mainly refers to the improvement of the ecological environment quality of abandoned mines through the preparation of restoration, land reclamation, and other measures [16][17]. ...
The escalating spread of industrial wastelands has spotlighted the need for effective ecological restoration. This paper introduces an evaluation system for assessing the environmental restoration benefits of such wastelands, integrating the entropy weight and optimal assignment method for index quantification. Enhancements to decision-making elements and the incorporation of the fuzzy comprehensive evaluation method have culminated in developing a D-FCE model-based ecological restoration benefit assessment model. An empirical analysis on selected sites revealed notable increases in soil organic carbon content post-restoration—ranging from 1.73% to 2.98% in ERL areas, 1.69% to 2.45% in GL areas, and 1.25% to 2.08% in AL areas—demonstrating significant carbon sequestration. Additionally, a 38% rise in ecological benefits was observed, translating to an economic boon of 8563.2 yuan/year. This study furnishes a scientific method for evaluating industrial wasteland restoration and underpins the formulation of pertinent policies.
... Recent monitoring and assessment of restoration efforts have focused more on vegetation coverage or greenness rather than on the chemical or biological indicators of vegetative conditions [19,20]. In particular, limited research is available on the rapid monitoring of C, N, and P in mixed plant communities within ecological restoration areas. ...
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.
... In scientific discourse, three primary terms are frequently associated with the usage of land following mining activities: restoration, reclamation, and rehabilitation [24,25,30,31]. Additionally, certain former mining sites are recognized as unique ecosystems, valued as cultural heritage monuments, and are thus granted protection [32] or serve as novel economic opportunities by transforming them in tourist attractions [33]. ...
... This focus separates post-mine rehabilitation from other restoration endeavors, attributing to the significant disturbance levels encountered. Consequently, recovery goals tend to favor the establishment of novel or hybrid ecosystems, comprising both native and non-native species, to ensure an acceptable degree of stability and ecosystem functionality [30,83]. ...
The rehabilitation of abandoned mining sites is an increasingly pressing issue in the context of sustainable development. Recent research have emphasized the need for a holistic approach to the abandoned mining sites and their environmental rehabilitation. Based on field analysis, environmental assessments, satellite imagery processing and geographic information operations, this paper pushes forward the existing knowledge by doing a comprehensive assessment of abandoned mining sites in the Romanian Carpathians and by proposing innovative and sustainable rehabilitation solutions. Our findings highlight that abandoned mining sites and their surrounding territories in the Romanian mountains have significant ecological imbalances and complex socio-economic issues. The findings also suggest that by adopting innovative, integrated, and sustainability-oriented approaches, territories affected by mining can be transformed into valuable and sustainable spaces to meet human needs. We conclude by presenting the importance of innovation in ecological reconstruction and spatial-functional reintegration of mining sites in mountain areas as a useful tool in making fair decisions, both in the context of implementing appropriate development policies as well as for resilience and environmental sustainability of mining-affected mountain areas.
... Restoration aims to create a self-sufficient ecosystem that can sustain itself without outside intervention [4]. Numerous countries have enacted legislation mandating mining companies adhere to strict criteria for restored topsoil, vegetation, and water quality following mine rehabilitation [5]. To accomplish these tasks, comprehensive management is required. ...
... This emerging reality is made possible by progress in computer vision, graphic processing, Figure 1. The yearly count of publications and the primary assessment techniques utilized for mine rehabilitation since the 1970s [5]. ...
... According to the authors' research, n studies have utilized LiDAR sensors for mine rehabilitation. McKenna, et al. [5] a et al. [47] have acknowledged this and suggested its importance. Therefore, it is n to evaluate the accuracy and quality of UAV data collection using LiDAR se capture images and create 3D spatial data. ...
In recent years, mine site closure and rehabilitation have emerged as significant global challenges. The escalating number of abandoned mines, exemplified by over 60,000 in Australia in 2017, underscores the urgency. Growing public concerns and governmental focus on environmental issues are now jeopardising sustainable mining practices. This paper assesses the role of unmanned aerial vehicles (UAVs) in mine closure, exploring sensor technology, artificial intelligence (AI), and
mixed reality (MR) applications. Prior research validates UAV efficacy in mining, introducing various deployable sensors. Some studies delve into AI’s use for UAV data analysis, but a comprehensive review integrating AI algorithms with MR methods for mine rehabilitation is lacking. The paper discusses data acquisition methods, repeatability, and barriers toward fully autonomous monitoring
systems for mine closure projects. While UAVs prove adaptable with various sensors, constraints such as battery life and payload capacity impact effectiveness. Although UAVs hold potential for AI testing in mine closure studies, these applications have been overlooked. AI algorithms are pivotal for creating autonomous systems, reducing operator intervention. Moreover, MR’s significance in mine closure is evident, emphasising its application in the mining industry. Ultimately, a hybrid
UAV–AI–MR technology is not only viable but essential for achieving successful mine closure and sustainable mining practices in the future.
... The method has the capacity to evaluate the extent of vegetation restoration, therefore offering a notable opportunity to better understand mine site reclamation and its potential for carbon sequestration. In the past few decades, there has been an increasing adoption of remote sensing methods for the purpose of detecting carbon sequestration and mine revegetation [6]. ...
Reclamation is regarded as one of the mining processes that can lessen the environmental impact of its production, particularly for large-scale coal mines that emit significant quantities of greenhouse gases. However, the assessment and evaluation of the reclamation process primarily rely on qualitative methods. Utilizing LANSAT8 Operational Land Imager (OLI) remote sensing in conjunction with GIS, this study aimed to develop a quantitative method for validating the efficacy of a reclamation procedure applicable to the emerging trend of carbon reduction. The empirical formula utilized to compute the annual carbon sequestrations of the reclamation area in the Mae Moh mine exhibited the appropriate spatial relative standard deviation (S-RSD) at 98.25%. The findings indicate that the reclamation area reached its highest level of carbon sequestration in 2022, at 331.28 ± 11.89 ktCO2e, surpassing the baseline of 126.53 ktCO2e. Furthermore, the approach demonstrates significant potential in improving the standard method for assessing reclamation through reforestation.
... The utilization of remote sensing is a crucial component of the environmental impact monitoring of mining activities, as well as assessing the effects of revitalization and remediation efforts in postmining areas. This is corroborated by the abundance of research published in these domains, particularly with respect to witnessing an increase in the period between 2010 and 2019, with the NDVI being the most utilized index [63]. This is further corroborated by studies conducted in regions proximate to the area analyzed in this study, such as research pertaining to the former Babina Mine in western Poland [64] or the active Bełchatów open-pit mine [65]. ...
The impact of mining effects is undoubtedly an important research topic, especially in the case of assessing the effects of postmining factors. This study examines the drought in the Olkusz region using satellite imagery (Sentinel-2) and remote sensing indices. The analysis reveals that the region experienced multiple types of drought, including hydrogeological drought due to groundwater level lowering caused by mining activities, agricultural drought resulting from insufficient soil moisture, hydrological drought characterized by reduced water flow in rivers, and meteorological drought linked to decreased precipitation and high temperatures. This study demonstrates the usefulness of optical imaging and remote sensing indices in monitoring and assessing drought conditions. The results indicate significant changes in vegetation health and water content, as well as alterations to the natural environment within the region. This research highlights the importance of considering both human-induced and natural factors when evaluating drought phenomena. Continued monitoring and expansion of the study area would provide valuable insights into the long-term effects of weather conditions and the broader impacts on the ecosystem.
... Plant species diversity is a fundamental goal for ecological restoration particularly in mining areas where functional and often biodiverse ecosystems need to be reinstated (Brancalion & Holl, 2020;Chen et al., 2022;Han et al., 2021;McKenna et al., 2020). Ensuring complete species mixes are reinstated in restoration programs can improve ecosystem function and stability, particularly for alleviating impacts of extreme or unexpected environmental events (Fremout et al., 2022;Gaston, 2000;Hauser et al., 2021;Isbell et al., 2015;Naeem et al., 1994). ...
The effective and efficient monitoring of revegetation outcomes is a key component of ecosystem restoration. Monitoring often involves labor-intensive manual methods, which are difficult to deploy when sites are inaccessible or involve large areas of revegetation. This study aimed to identify plant species and quantify α-diversity index on a sub-meter scale at Manlailiang Mine Site in Northwestern China using unmanned aerial vehicles (UAVs) as a means to semiautomate large-scale vegetation monitoring. UAVs equipped with multispectral sensors were combined with three industry-standard supervised classification algorithms (support vector machine [SVM], maximum likelihood, and artificial neural network) to classify plant species. Spectral vegetation indices (normalized difference vegetation index [NDVI], difference vegetation index [DVI], visible-band difference vegetation index, soil-adjusted vegetation index, modified soil-adjusted vegetation index, and excess green-excess red) were used to assess vegetation diversity obtained from on-ground survey plot data (the Margalef, Pielou, Simpson, and Shannon-Wiener indices). Our results showed that SVM outperformed other algorithms in species identification accuracy (overall accuracy of 84%). Significant relationships were observed between vegetation indices and diversity indices, with the DVI performing significantly better than many more commonly used indices such as the NDVI. The findings highlight the potential of combining UAV multispectral data, spectral vegetation indices and ground surveys for effective and efficient fine-scale monitoring of vegetation diversity in the ecological restoration of mining areas. This has significant practical benefits for improving adaptive management of restoration through improved monitoring tools.
... 4). the result of both a preliminary analysis and a literature review. According to the works published so far, the NDVI is the most widely used vegetation index to examine the state of the flora in post-mining areas (Buczyńska, 2020;McKenna et al., 2020). On the other hand, studies (Ma et al., 2017;Zhang Yao and Zhou Wei, 2016) proved that the SAVI, MSR, SR, NLI and VARI indices do not properly reflect the condition of multi-species and tall vegetation. ...
The Babina mine closed almost 50 years ago, and reclamation works for reforestation began shortly after. Despite various technical and biological measures, the area is still experiencing negative consequences from mining, exacerbated by its complex glaciotectonic structure. These phenomena have an impact on the post-mining environment. The presented study aimed to identify areas within a mining area of the Babina mine, where the former mining activities and geological structure had the strongest influence on the changes in flora and soil conditions between 1989 and 2019. The research also revealed previously undocumented mining excavations. The study used the Mining and Geology Impact Factor, combining OLS models and spatial statistics based on spectral indices. Eighteen explanatory factors described the geological-mining and topographic conditions, while five dependent variables represented changes in vegetation and soil over 30 years. MaGIF values ranged between 0.13 and 0.97. The highest values indicated a significant impact on soil and vegetation in six regions. Extrapolation of the index values identified three areas where past mining activities may have occurred outside of archival records. This study confirms the substantial environmental influence of previous mining and the glaciotectonic structure. The use of remote sensing and spatial analysis aids in identifying vulnerable areas and preventing potential environmental damage.
... This deficiency can be attributed to the lack of adequate sustainable oversight in the ecological restoration stage. Compared to international mine ecological restoration works (McDonald & Williams 2009;McKenna et al. 2020), China's mine restoration initiatives started later. However, China has displayed a more proactive attitude and taken decisive action in terms of capital investment and policy implementation for mine restoration projects (Hu et al. 2012;Zhao et al. 2020). ...
With the exploitation of rare earth elements (REE) in southern China, desertification has become a serious ecological problem in this region. To accurately understand the desertification process in mining areas and formulate targeted ecological restoration programs, taking the Lingbei mining area in Ganzhou City, Jiangxi Province as the study area, we explored desertification information extraction methods, desertification dynamics monitoring, and desertification drivers in REE mining areas using multisource data from 1986 to 2021. The results show that from the method of extracting desertification information, Random Forest is the prominent (83.33%), followed by Albedo–NDVI (Normalized Difference Vegetation Index) space (74.44%), and thirdly Linear Spectral Mixture Model (65.56%). From 1986 to 2021, the desertification land area in Lingbei mining areas first increased and then decreased, showing a reverse trend, but it has not recovered to the pre-mining level. The government's ecological reclamation measures are the key factors for the restoration of desertification land. There are still 17.81 km2 areas that have not been restored, of which 2.16 km2 are at the level of severe desertification. Moderate desertification and light desertification have not been completely curbed, which needs continuous attention. Vegetation coverage has the highest explanatory power to the distribution of land desertification in mining areas, followed by land use classification, indicating that human activities have a great influence on the spatial differentiation of land desertification in mining areas, and it is necessary to pay attention to regional balanced and sustainable development in the future.
