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The vegetation cover dynamics such as the spatial extent and pattern of disturbance and recovery are necessary information in mining regulation and environmental sustainability assessment. The acquisition and further analysis of these dynamics are hampered due to that the vegetation cover in mining area changes both spatially and temporally. This paper aims to assess the capability of LandTrendr algorithm and Landsat imagery in surface mining area to detect the vegetation change and characterize the historical dynamics. Curragh coal mine site in Australia was taken as an illustrative application. The spatial extent, change pattern and attributes of vegetation disturbance and recovery during 1989–2014 were detected and mapped. The overall accuracy for disturbance and recovery classification are 85.21% and 86.59% respectively. The results show that more than 2982 ha out of 4573 ha of disturbed land in entire Curragh had been covered by vegetation, while 95% of the oldest part of the operation (Central Curragh) has been seeded and rehabilitated. The average value of cumulative Disturbance to Recovery ratio for entire Curragh mine site was about 59%. This suggests that the Curragh mine has been complying with mining legislation by undertaking progressive rehabilitation and vegetation establishment efforts. The advantage of LandTrendr is that it relies on free data from Landsat archive and has straightforward operating procedures. It can provide environmental assessment and rehabilitation with serviceable data including raster maps, yearly data, cumulative Disturbance to Recovery ratio and change attributes. The LandTrendr algorithm and Landsat imagery could be supplemented with field validation and study such as recovery success analysis to facilitate better environmental assessment and mining sustainability.

In-situ monitoring of the environmental impact is essential for the verification of clean operation of carbon capture and storage (CCS) projects. We conducted an empirical study based on remotely sensed data and field observations from an enhanced oil recovery (EOR) site in China. Geostatistical analysis and general linear model regression were performed to detect the impact of fugitive CO2 emission from oil buffer tanks. Results show that the emitted CO2 resulted in CO2 enrichment about 25–100 m away from the buffer tanks. The spatial pattern and semivariogram parameters of normalized differential vegetation index (NDVI) in the CCS core operating area had not been altered significantly. The CO2 concentration is not a statistically significant explanatory factor for the variation of wheat growth in the present CCS-EOR site that located in Gaoqing County in the east of China. The impact of fugitive CO2 emission on wheat growth appears limited because of the instability and rapid diffusion of emitted CO2. However, we emphasize that these results were extracted from the in-situ monitoring that characterized by macro-level and short term. Long-term biology-based study at a micro-level is imperative for further understanding and determining the environmental impact of fugitive CO2 emission. Moreover, considering the incidental CO2 breakthrough and the unknown impact of emitted gas, including CO2 and hydrocarbons, on the quality of wheat plant and grain, long-time field monitoring, and improvement of production equipment and technique are essential to ensure the clean production of CCS-EOR.

Estimation of the ecological and environmental damage is viewed as an essential tool for effective decision-making in ecological restoration, especially involving high-intensity coal mining and high ecological vulnerability on the Loess Plateau, China. Using the Datong mining area on the Loess Plateau as a case study, we propose an integrated spatial estimation based on surface subsidence prediction, geographic information system, and field survey. The implications for regional ecological restoration are analyzed. Based on this inspection, the magnitude of ecological and environmental damage depended on a combination of risk factors, other than a single factor or evaluation target. Still, the geological hazard was the primary impact factor, especially surface subsidence as a result of underground mining. The results suggest that areas of severe, moderate, and slight damage accounted for 9.87%, 80.09%, and 10.04%, respectively. The methodology used was effective in determining the ecological and environmental damage that is consistent with the spatial distribution of subsidence. The proposed integrated estimation provides targeted measures for active, progressive, and passive interventions to improve and renovate the post-reclamation mining ecosystem and ensure sustainable planning in underground mining areas.

Environmental sustainability is a mandatory consideration for Carbon Capture and Storage (CCS) project, thereby making environmental monitoring more essential. This paper aims at demonstrating the feasibility and superiority of Synthetic Aperture Radar (SAR) technique for environmental monitoring of enhanced oil recovery (EOR) project. Surface deformation and topsoil moisture are considered as the monitoring factors due to their importance to the public security and sustainability. Taking Jingbian CO 2 -EOR project as a case study, Interferometric SAR (InSAR) and Advanced Integral Equation Model (AIEM) were used for spatial estimates of surface deformation and topsoil moisture from Sentinel-1A images. The results showed that the distribution of surface deformation and topsoil moisture both manifested as spatial heterogeneity. No significantly regular uplift or subsidence trend was observed within the storage fields. The average deformation velocity of 5.63 mm yr −1 from 537 measuring points was probably determined by the trade-off between soil erosion and eolian dust deposit. Topsoil moisture was observed to associate with natural conditions, and its spatial distribution was mainly ruled by topographic factors. Areas with soil moisture below 20% covered about 3.98 km 2 , totally accounting for 77.14%. Areas with soil moisture over 20% were mostly distributed in the gully regions. In conclusion, currently, there was no large deformation trend or abnormal topsoil moisture distribution as public concerns, but long-term monitoring program is still needed for ensuring environmental sustainability. This study demonstrates that SAR technique can improve the spatial knowledge of surface deformation and topsoil moisture, which is useful for sustainability assessment of operating CO 2 -EOR project.