Remote Sensing of Mine Site Rehabilitation for Ecological Outcomes: A Global Systematic Review

Remote sensing of artisanal and small-scale mining: A review of scalable mapping approaches

Artisanal and small-scale mining (ASM) significantly influences the socio-economic development of many low-to-middle-income countries, albeit sometimes at the expense of environmental and human health. Characterized by its labor-intensive extraction from confined (<5 ha) or peripheral mineral reserves, congregated ASM practices can rival the spatial footprint of industrial mines. The unregulated and informal nature of many ASM activities presents monitoring challenges that remote sensing (RS) methods aim to address. While local-scale ASM mapping has seen success, scaling these methods to regional or global levels remains unclear. We review literature on mapping ASM to determine: (1) if studies represent the global distribution and diversity of ASM activities, (2) how ASM's unique characteristics influence the choice of RS methods, and (3) which RS approaches are the most accurate and cost-effective. We found current studies disproportionately focused on ASM regions in Africa, which highlights the need to extend the research to other regions with unique ASM characteristics, such as coal and sand mining in India and China. The selection of RS approaches is heavily influenced by local ASM contexts, the scale of analysis, and resource constraints such as funding for high-resolution imagery and validation data availability. We argue that accurate regional-scale ASM mapping (>100,000 km2) requires innovative combinations of data and methods to overcome data management and storage challenges. Local community participation, including miners, is vital for on-ground mapping and monitoring capacity. We outline a research agenda needed to develop a range of approaches for mapping and monitoring ASM in under-studied regions. By synthesizing effective methods, we provide a foundation for generating accurate and comprehensive spatial data, addressing the issues of inaccurate and incomplete data that global ASM platforms aim to resolve. This spatial data can guide policymakers, NGOs, and businesses in making informed decisions and targeted interventions to improve ASM sector safety, sustainability, and efficiency. Leveraging cloud-based geoprocessing platforms, with regularly updated global satellite image archives, combined with crowd-sourced on-ground information offers a potential solution for sustained regional-scale monitoring.

Low-Cost Sensors Technologies for Monitoring Sustainability and Safety Issues in Mining Activities: Advances, Gaps, and Future Directions in the Digitalization for Smart Mining

Nowadays, monitoring aspects related to sustainability and safety in mining activities worldwide are a priority, to mitigate socio-environmental impacts, promote efficient use of water, reduce carbon footprint, use renewable energies, reduce mine waste, and minimize the risks of accidents and fatalities. In this context, the implementation of sensor technologies is an attractive alternative for the mining industry in the current digitalization context. To have a digital mine, sensors are essential and form the basis of Industry 4.0, and to allow a more accelerated, reliable, and massive digital transformation, low-cost sensor technology solutions may help to achieve these goals. This article focuses on studying the state of the art of implementing low-cost sensor technologies to monitor sustainability and safety aspects in mining activities, through the review of scientific literature. The methodology applied in this article was carried out by means of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and generating science mapping. For this, a methodological procedure of three steps was implemented: (i) Bibliometric analysis as a quantitative method, (ii) Systematic review of literature as a qualitative method, and (iii) Mixed review as a method to integrate the findings found in (i) and (ii). Finally, according to the results obtained, the main advances, gaps, and future directions in the implementation of low-cost sensor technologies for use in smart mining are exposed. Digital transformation aspects for data measurement with low-cost sensors by real-time monitoring, use of wireless network systems, artificial intelligence, machine learning, digital twins, and the Internet of Things, among other technologies of the Industry 4.0 era are discussed.

Application of integrated spatial analysis and NDVI for tree monitoring in reclamation area of coal mine

Reclamation, defined as one of the important processes in mining, is commonly conducted to regain the value of the land after natural resource extraction. The process involves many activities such as reforestation, remediation, and land transformation. Even supposing that those processes can be monitored, thus some of the progress in those activities cannot be numerically evaluated, especially for reforestation. Mae Moh mine, the largest coal mine in Southeast Asia, is in the early stage of reclamation where a large scale of reforestation must be accomplished. However, the monitoring and evaluation of the improvement of those areas are based on manual field observation which is time-consuming and inefficient. For a purpose of subsiding the conventional method, integrated spatial technology was assigned as the main tool in defining the effective indirect method for monitoring and evaluating the reforested area. In this study, the remote sensing techniques, based on satellite-images and multispectral-UAV, were compared to define the most appropriate data collecting method which will be assigned as the main tool for gathering the data over the reforestation area of Giant crepe-myrtle, Indian cork Tree, Laza wood, and Teak. These collected data were further analyzed into normalized difference vegetation index (NDVI) and used as the dependent variable for linear regression with significant parameters, affecting the growth of the reforested species. The results of the study defined that the suitable collecting method is the multispectral-UAV which can give %RSD of NDVI range from 16.58 to 40.75. In accordance with the analysis, the R² of the regression modeling for each species ranged from 0.568 to 0.831, which can determine the feasibility of assigning the model for the indirect monitoring scheme for the reclamation.

Using POI and time series Landsat data to identify and rebuilt surface mining, vegetation disturbance and land reclamation process based on Google Earth Engine

The development of coal resources is necessary, but it has a huge negative impact on land, ecology, and the environment. With the increasing awareness of environmental protection and the requirements of related regulations, the design and practice of reclamation projects run through the mining life cycle and continue for a long time after the coal production. High-precision monitoring of mining disturbance and reclamation, quantifying the degree and time of vegetation disturbance and restoration, is of great significance to minimize the environmental effect of mining. Remote sensing, widely used as efficient monitoring tool, but there is not enough research on disturbance and reclamation monitoring taking into account large-scale areas and high temporal and spatial accuracy. Especially when mining sites remain unknown, how to distinguish the disturbance of coal mining and other human activities affecting the surface land cover has become a challenge. Therefore, this paper proposed a method to reconstruct the time series of mining disturbance and reclamation in a large area by using the POI (point of interest) and Landsat time series images using multiple buffer analysis methods. The process includes: (1) Retrieval of POI in the study area based on the public mining list using Python crawler, and buffering 100 km for preliminary extraction of potential mining areas; (2) Using spectral index mask and random forest algorithm to accurately extract the exposed coal on the Google Earth Engine (GEE) platform; (3) Buffering 10 km to identify the occurrence of disturbance and reclamation, using pixel-based temporal trajectory identification of LandTrendr algorithm under GEE. The method successful detect the change points of surface coal mining disturbance and reclamation in eastern Inner Mongolia of China. The results show that: (1) The method can effectively identify the extent of surface coal mining disturbance and reclamation, and the overall extraction accuracy is 81%. (2) Surface coal mining disturbance in eastern Inner Mongolia was concentrated in 2006-2011. By 2020, the total disturbed area is 627.8 km², with an average annual disturbance of 18.5 km², and the annual maximum disturbance to the ground reached 64.6 km² in 2008. With the total reclaimed area being 236.3 km², the reclamation rate is about 37.6%. This study provides a systematic solution and process for monitoring the disturbance and reclamation of surface coal mining in a large range with little known about the mines' location. It can effectively identify the mining disturbance and reclamation process which can also be extended to other areas, providing a quantitative assessment of mining disturbance and reclamation, which can support further ecological restoration decision-making.

Modelling regional ecological security pattern and restoration priorities after long-term intensive open-pit coal mining

Long-term intensive open-pit mining can have huge impacts on ecosystems and the services they provide, affecting the integrity of ecosystem structures, functions and process and thus the "ecological security" of a whole mining region. The indirect and direct impacts of mining are spatially and temporally complex and therefore ecological security patterns need to be considered. However, to date there has been little research focusing on ecological security patterns in mining regions. This study aims to model and map ecological security and restoration priorities in an intensive open-cut coal mining region accounting for spatio-temporal changes of multiple ecosystem services. Four ecosystem services including habitat quality, carbon sequestration, water yield, and sediment retention were assessed and mapped in 1990, 2000, 2010, and 2020. Next ecological security patterns and restoration priorities were modelled and characterized using the Self-Organizing Feature Map to identify ecological sources, and circuit theory in Linkage Mapper to characterize connectivity and flows. The results showed that habitat quality, carbon sequestration, and water yield services were most affected by vegetation cover changes due to mining exploitation, while sediment retention was influenced by multiple natural factors, especially topography. Ecological sources, corridors, pinch-points and barriers showed various changing trends due to mined and built-up land expansion over time. Ecological source area declined from 1355.08km² in 2000 to 584.92 km² in 2020, while the number of corridors increased from 17 in 2000 to 25 in 2010 and then decreased to 21 in 2020. Although restoration has been conducted on some mine sites, regional-scale restoration needs greater consideration. This study provides decision-makers and stakeholders with a method for assessing regional-scale ecological security and restoration in a holistic and systematic way moving beyond a single mine, which is critical for balancing ecological security protection with minerals production in intensive mining regions.

Monitoring of Vegetation Disturbance and Restoration at the Dumping Sites of the Baorixile Open-Pit Mine Based on the LandTrendr Algorithm

Overstocked dumping sites associated with open-pit coal mining occupy original vegetation areas and cause damage to the environment. The monitoring of vegetation disturbance and restoration at dumping sites is important for the accurate planning of ecological restoration in mining areas. This paper aimed to monitor and assess vegetation disturbance and restoration in the dumping sites of the Baorixile open-pit mine using the LandTrendr algorithm and remote sensing images. Firstly, based on the temporal datasets of Landsat from 1990 to 2021, the boundaries of the dumping sites in the Baorixile open-pit mine in Hulunbuir city were extracted. Secondly, the LandTrendr algorithm was used to identify the initial time and duration of vegetation disturbance and restoration, while the Normalized Difference Vegetation Index (NDVI) was used as the input parameter for the LandTrendr algorithm. Thirdly, the vegetation restoration effect at the dumping sites was monitored and analyzed from both temporal and spatial perspectives. The results showed that the dumping sites of the Baorixile open-pit mine were disturbed sharply by the mining activities. The North dumping site, the South dumping site, and the East dumping site (hereinafter referred to as the North site, the South site, and the East site) were established in 1999, 2006, and 2010, respectively. The restored areas were mainly concentrated in the South site, the East site, and the northwest of the North site. The average restoration intensity in the North site, South site, and East site was 0.515, 0.489, and 0.451, respectively, and the average disturbance intensity was 0.371, 0.398, and 0.320, respectively. The average restoration intensity in the three dumping sites was greater than the average disturbance intensity. This study demonstrates that the combination of temporal remote sensing images and the LandTrendr algorithm can follow the vegetation restoration process of an open-pit mine clearly and can be used to monitor the progress and quality of ecological restoration projects such as vegetation restoration in mining areas. It provides important data and support for accurate ecological restoration in mining areas.

Study of Chemical Pollutants and Ecological Reconstruction Methods in the Tismana I Quarry, Rovinari Basin, Romania

The phytoremediation of polluted land in Romania is based on research on biodiversity, environmental protection, and the sustainable use of natural or man-made resources, carried out by universities and research institutes for over 30 years, synchronized with those at the European and global level. The aim of this paper is to establish the categories of pollutants with potential environmental, economic, and social impacts associated with mining in order to choose the optimal method of ecological reconstruction. In this regard, the Tismana quarry was mapped, the surface of the analysis plot was set at 50 m × 50 m, and the sampling depth was 0–20 cm; from each plot, two samples were collected. Out of a total of 121 analysis plots, ten susceptible plots were identified, from which 20 samples were collected and analyzed. The samples were analyzed by the UV-VIS spectrophotometer method—MLUV1720 and UV spectrometry—with a SHIMADZU UV 160U spectrophotometer; they indicated in only three analysis plots a pollution with phenols, Ni, Zn, Ni and HAP, the concentrations of which exceeded only the normal values, which does not affect the eaves threshold and intervention for the type of land use. Being point pollution, the phytoremediation of these soils can be achieved in a short time. The paper aims to present the situation of chemical pollutants in the Tismana quarry area, and to offer different ecological rehabilitation solutions depending on their presence.

Remote Sensing Monitoring of the Spatial Pattern of Greening and Browning in Xilin Gol Grassland and Its Response to Climate and Human Activities

As a unique ecosystem with multiple ecological functions but high fragility, grassland in arid areas is very vulnerable to changes in the natural environment or human activities, resulting in various ecological and environmental problems. In order to study the degree and spatial extent of the influence of climatic conditions and human activities, especially mining activities, on grasslands in arid regions, we used remote sensing data to monitor the vegetation of the Xilin Gol grassland over a long period. The significant greening and browning areas of Xilin Gol grassland vegetation from 2000 to 2020 were extracted by a time series analysis. At the same time, the correlation analysis method was used to obtain the response of the Xilin Gol grassland vegetation to climatic factors and social and economic factors. In addition, we propose a new method based on buffer analysis and correlation analysis to calculate the influence range of vegetation degradation due to mining. We used this method to determine the influence range of vegetation degradation in the main mining area of the Xilin Gol grassland. The results showed that the vegetation condition of the Xilin Gol grassland were slightly improved from 2000 to 2020. Its vegetation was significantly affected by precipitation, and more than 50% of the area’s vegetation changes were highly correlated with precipitation changes. However, the area with the most serious vegetation degradation was mainly affected by human factors, and this part accounted for about 0.13% of the total area. In the form of direct damage and indirect effects (pulling population and economic growth to expand built-up areas), coal mining has become the main driving factor in the most significant areas of vegetation damage in the study area. Vegetation coverage in areas with significant greening and significant browning was highly correlated with economic factors, indicating that the vegetation changes were significantly affected by economic development. This study can reflect the vegetation changes and main driving factors in the overall and key areas of the Xilin Gol League and is a meaningful reference for the local balance of economic development and environmental protection.

The Influence of Burn Severity on Post-Fire Spectral Recovery of Three Fires in the Southern Rocky Mountains

Increased wildfire activity and altered post-fire climate in the Southern Rocky Mountains has the potential to influence forest resilience. The Southern Rocky Mountains are a leading edge of climate change and have experienced record-breaking fires in recent years. The change in post-fire regeneration and forest resilience could potentially include future ecological trajectories. In this paper, we examined patterns of post-fire spectral recovery using Landsat time series. Additionally, we utilized random forest models to analyze the impact of climate and burn severity on three fire events in the Southern Rocky Mountains. Fifteen years following the fires, none of the burned stands fully recovered to their pre-fire spectral states. The results suggested that burn severity significantly impacted post-fire spectral recovery, but that influence may decrease as time since fire increases. The biggest difference in forest recovery was among fire events, indicating that post-fire climate may be influential in post-fire recovery. The mean and minimum growing-season temperatures were more significant to post-fire recovery than the variability in precipitation, which is consistent with field-based analysis. The present study indicated that, as warming continues, there may be changes in forest density where forests are not regenerating to their pre-fire spectral states. Additionally, this study emphasizes how high-elevation forests continue to regenerate after fires, but that regeneration is markedly affected by post-fire climate.

Managing and Reforesting Degraded Post-Mining Landscape in Indonesia: A Review

Tropical forests are among the most diverse ecosystems in the world, completed by huge biodiversity. An expansion in natural resource extraction through open-pit mining activities leads to increasing land and tropical forest degradation. Proper science-based practices are needed as an effort to reclaim their function. This paper summarizes the existing practice of coal mining, covering the regulatory aspects and their reclamation obligations, the practices of coal mining from various sites with different land characteristics, and the reclamation efforts of the post-mining landscapes in Indonesia. The regulations issued accommodate the difference between mining land inside the forest area and outside the forest area, especially in the aspect of the permit authority and in evaluating the success rate of reclamation. In coal-mining practices, this paper describes starting from land clearing activities and followed by storing soil layers and overburden materials. In this step, proper handling of potentially acid-forming materials is crucial to prevent acid mine drainage. At the reclamation stage, this paper sequentially presents research results and the field applications in rearranging the overburden and soil materials, controlling acid mine drainage and erosion, and managing the drainage system, settling ponds, and pit lakes. Many efforts to reclaim post-coal-mining lands and their success rate have been reported and highlighted. Several success stories describe that post-coal-mining lands can be returned to forests that provide ecosystem services and goods. A set of science-based best management practices for post-coal-mine reforestation is needed to develop to promote the success of forest reclamation and restoration in post-coal-mining lands through the planting of high-value hardwood trees, increasing trees’ survival rates and growth, and accelerating the establishment of forest habitat through the application of proper tree planting technique. The monitoring and evaluation aspect is also crucial, as corrective action may be taken considering the different success rates for different site characteristics.