Evaluation and dynamic monitoring of ecological environment quality in mining area based on improved CRSEI index model

Liu, Yajing; Liu, Hongjian; Yan, Chaoqun; Feng, Zhengwen; Zhou, Shuai

doi:10.1016/j.heliyon.2023.e20787

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…This is consistent with the findings of Niu et al [103] and Song et al [104]. With the promotion of the concept of sustainable development, ecological restoration of mining areas is imperative [105]. When managing the ecological environment of mining cities, special attention should also be paid to the ecological condition of the areas closer to the mining area.…”

Section: Impact Of Mining Activities On the Quality Of The Ecological...supporting

confidence: 90%

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

Zeng,

Dai,

et al. 2024

Sustainability

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The environmental quality of a mining city has a direct impact on regional sustainable development and has become a key indicator for assessing the effectiveness of national environmental policies. However, against the backdrop of accelerated urbanization, increased demand for resource development, and the promotion of the concept of ecological civilization, mining cities are faced with the major challenge of balancing economic development and ecological environmental protection. This study aims to deeply investigate the spatial and temporal variations of environmental quality and its driving mechanisms of mineral resource-based cities. This study utilizes the wide coverage and multitemporal capabilities of MODIS optical and thermal infrared remote sensing data. It innovatively develops the remote sensing ecological index (RSEI) algorithm on the PIE-Engine cloud platform to quickly obtain the RSEI, which reflects the quality of the ecological environment. The spatial and temporal evolution characteristics of the environmental quality in seven typical mining cities in China from 2001 to 2022 were analyzed. Combined with the vector mine surface data, the spatial and temporal variability of the impacts of mining activities on the ecological environment were quantitatively separated and explored. In particular, the characteristics of mining cities were taken into account by creating buffer zones and zoning statistics to analyze the response relationship between RSEI and these factors, including the distance to the mining area and the percentage of the mining area. In addition, the drivers and impacts of RSEI in 2019 were analyzed through Pearson correlation coefficients pixel by pixel with 10 factors, including natural, economic, and mining. Regression modeling of RSEI in 2019 was performed using the random forest (RF) model, and these drivers were ranked in order of importance through random forest factor importance assessment. The results showed that (1) the ecological quality of mining cities changed significantly during the study period, and the negative impacts of mining activities on the ecological environment were significant. (2) The areas with low RSEI values were closely related to the mining areas and cities. (3) The RSEI in the mining areas of mining cities was generally lower than the average level of the cities. The RSEI gradually increased as the distance to the mine site increased. (4) The increase in the size of the mine area initially exacerbates the impact on the ecological environment, but the impact is weakened beyond a certain threshold. (5) The distance to the mining area is the most important factor affecting the quality of the ecological environment, followed by DEM, GDP, and precipitation. This study is of great importance for advancing sustainable development in mining cities and formulating sustainable strategies.

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Section: Impact Of Mining Activities On the Quality Of The Ecological...supporting

confidence: 90%

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

Zeng,

Dai,

et al. 2024

Sustainability

View full text Add to dashboard Cite

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“…Compared with the traditional RSEI method, the improved RSEI method is more applicable to the mining area. Secondly, from the results of principal component analysis, the calculation results of the first principal component are relatively stable, which is different from the calculation results of the previous index constructed by traditional methods (Liu et al, 2023). The LISA cluster maps.…”

Section: Comparison With Traditional Remote Sensing Ecological Index ...mentioning

confidence: 79%

“…In the previous literature, human engineering activities have caused serious damage to the ecological environment, such as coal mining (Liu et al, 2023), urban sprawl (Lin et al, 2022), and climate rise caused by excessive carbon dioxide emissions (Zhang et al, 2023). However, with the strict implementation of laws, regulations and policies such as ecological environmental protection, the quality of the ecological environment has a tendency to improve (Wang et al, 2021).…”

Section: Figure 10mentioning

confidence: 99%

Ecological environment quality assessment and spatial autocorrelation of northern Shaanxi mining area in China based-on improved remote sensing ecological index

Zhu,

Cao,

Yang

et al. 2024

Front. Environ. Sci.

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The northern Shaanxi coal mining area is an important coal production base in China and an ecologically fragile area, and it is of great significance to explore the ecological environment quality and spatial evolution trend of the mining area. Based on Sentinel-2 and MODIS image data, an improved remote sensing ecological index was constructed by principal component analysis method: normalized difference vegetation index, normalized difference water index, normalized differential buildup and bare soil index, and net primary productivity. The ecological environment quality of the northern Shaanxi coal mining area and its influencing factors, as well as the spatial autocorrelation analysis of ecological environment quality, were discussed. The results showed that: 1) The vegetation coverage in the study area showed an overall increasing trend, but it was greatly affected by the average annual temperature. The NDVI index at the mine area is higher than the NDVI index at the non-mine area. 2) The water area gradually decreases with the year, which has a certain negative correlation with the total raw coal production. 3) The NDBB index showed a decreasing trend with the year, and compared with the non-mining area. 4) The coupling of year-by-year precipitation and temperature leads to interannual fluctuation of NPP value. 5) The change of ecological environment quality in the study area is the result of the comprehensive effect of natural factors and human factors. The implementation of ecological protection projects such as geological environmental protection and land reclamation in mining areas also has a certain impact on the trend of ecological environment quality. 6) There was a significant spatial autocorrelation in the quality of the ecological environment in the study area. There are significant “High-High” gathering areas of ecological environment quality within the coal mining area.

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“…In addition, harmful organisms should be eliminated or controlled to maintain good ecological functions and biodiversity [65,66]. Also, the environments surrounding restored mountains should be comprehensively protected by clarifying the scope of their protection and monitoring systems, and by formulating natural disaster prevention and control measures [67,68]. Then, to a certain extent, safety hazards may be prevented.…”

Section: Integrated Pathways For Ecosystem Restorationmentioning

confidence: 99%

Integrated Assessment and Restoration Pathways for Holistic Ecosystem Health in Anxi County, China

Zhu,

Zhang,

Wang

et al. 2023

Sustainability

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Different types of ecosystems form a complex community of life. Hence, ecosystem protection and restoration should not focus solely on a single ecosystem. Ecosystem health assessments should consider the integrity and systematicity of interrelated ecosystems to inform rational environmental planning and management. In this study, the key characteristic indicators of major ecosystems (mountain, water, forest, and cropland) and ecosystem service capacity indicators in Anxi County, China, were selected to construct an integrated assessment system of ecosystem health that led to integrated ecosystem restoration pathways that addressed the county’s ecological problems. The results revealed that ecosystem health was higher in the western and lower in the eastern parts of the county. Throughout the county, “medium” and “poor” ecosystem health levels predominated, revealing that overall ecosystem sustainability was weak. Ecosystem restoration programmes should be tailored to each health level. Where there was “excellent” and “good” ecosystem health ratings, those healthy ecosystem functions should be strengthened and maintained. In the “medium” health areas, the control and prevention of ecological problems should be strengthened. “Poor” health areas require immediate integrated ecological restoration projects that ensure the connectivity and coordination of restoration tasks in fragile ecosystems. This then will enhance holistic ecosystem stability and sustainability.

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Evaluation and dynamic monitoring of ecological environment quality in mining area based on improved CRSEI index model

Cited by 4 publications

References 12 publications

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

Ecological environment quality assessment and spatial autocorrelation of northern Shaanxi mining area in China based-on improved remote sensing ecological index

Integrated Assessment and Restoration Pathways for Holistic Ecosystem Health in Anxi County, China

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