Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification
Understanding the impacts of land use and land cover changes on ecosystem service values (ESVs) is crucial for effective ecosystem management; however, the intricate relationship between these factors in coal mining regions remains underexplored. In particular, the influence of coal mining activitie...
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MDPI AG
2025-03-01
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| author | Shi Chen Jiwei Qin Shuning Dong Yixi Liu Pingping Sun Dongze Yao Xiaoyan Song Congcong Li |
| author_facet | Shi Chen Jiwei Qin Shuning Dong Yixi Liu Pingping Sun Dongze Yao Xiaoyan Song Congcong Li |
| author_sort | Shi Chen |
| collection | DOAJ |
| description | Understanding the impacts of land use and land cover changes on ecosystem service values (ESVs) is crucial for effective ecosystem management; however, the intricate relationship between these factors in coal mining regions remains underexplored. In particular, the influence of coal mining activities on these dynamics is insufficiently understood, leaving a gap in the literature that hinders the development of robust management strategies. To address this gap, we investigated the interplay between land use change and the ESV at the interface of Yang Coal Mine No. 2 and the Shanxi Yalinji Guanshan Provincial Nature Reserve in Yangquan City, Shanxi Province. Using Landsat 8 remote sensing data from 2013 to 2021, our approach incorporated analyses using the Google Earth Engine (GEE) platform. We employed a random forest algorithm to classify land use patterns and calculated key indices—including the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), enhanced vegetation index (EVI), and bare soil index (BSI)—which were combined with topographic features. Land use change dynamics were quantified via a transfer matrix, while changes in the ESV were evaluated using the ecosystem sensitivity index and ecological contribution rate. Our results revealed notable fluctuations: forestland increased from 2013 to 2018 before declining sharply from 2019 to 2021; grassland displayed similar variability; and constructed land experienced a continual expansion. Correspondingly, the overall ESV increased by 28.6% from 2013 to 2019, followed by a 19.5% decline in 2020 and 2021, with forest and grassland’s ESVs exhibiting similar trends. These findings demonstrate that land use changes, particularly those that are driven by human activities such as coal mining, have a significant impact on ecosystem service values in mining regions. By unraveling the nuanced relationship between land use dynamics and ESVs, our study not only fills the gap in the literature but also provides valuable insights for developing more effective ecosystem management strategies, ultimately advancing our understanding of ecosystem dynamics in human-impacted landscapes. |
| format | Article |
| id | doaj-art-cfb9d046aa7a4d5ebb1cb908197d775d |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-cfb9d046aa7a4d5ebb1cb908197d775d2025-08-20T03:03:25ZengMDPI AGRemote Sensing2072-42922025-03-01177113910.3390/rs17071139Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine ClassificationShi Chen0Jiwei Qin1Shuning Dong2Yixi Liu3Pingping Sun4Dongze Yao5Xiaoyan Song6Congcong Li7College of Water Resources and Architectural Engineering, Northwest A&F University, Xianyang 712100, ChinaCollege of Water Resources and Architectural Engineering, Northwest A&F University, Xianyang 712100, ChinaXi’an Research Institute of China Coal Technology and Engineering Group Corporation, Xi’an 710054, ChinaCollege of Water Resources and Architectural Engineering, Northwest A&F University, Xianyang 712100, ChinaSchool of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaCollege of Water Resources and Architectural Engineering, Northwest A&F University, Xianyang 712100, ChinaCollege of Water Resources and Architectural Engineering, Northwest A&F University, Xianyang 712100, ChinaKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaUnderstanding the impacts of land use and land cover changes on ecosystem service values (ESVs) is crucial for effective ecosystem management; however, the intricate relationship between these factors in coal mining regions remains underexplored. In particular, the influence of coal mining activities on these dynamics is insufficiently understood, leaving a gap in the literature that hinders the development of robust management strategies. To address this gap, we investigated the interplay between land use change and the ESV at the interface of Yang Coal Mine No. 2 and the Shanxi Yalinji Guanshan Provincial Nature Reserve in Yangquan City, Shanxi Province. Using Landsat 8 remote sensing data from 2013 to 2021, our approach incorporated analyses using the Google Earth Engine (GEE) platform. We employed a random forest algorithm to classify land use patterns and calculated key indices—including the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), enhanced vegetation index (EVI), and bare soil index (BSI)—which were combined with topographic features. Land use change dynamics were quantified via a transfer matrix, while changes in the ESV were evaluated using the ecosystem sensitivity index and ecological contribution rate. Our results revealed notable fluctuations: forestland increased from 2013 to 2018 before declining sharply from 2019 to 2021; grassland displayed similar variability; and constructed land experienced a continual expansion. Correspondingly, the overall ESV increased by 28.6% from 2013 to 2019, followed by a 19.5% decline in 2020 and 2021, with forest and grassland’s ESVs exhibiting similar trends. These findings demonstrate that land use changes, particularly those that are driven by human activities such as coal mining, have a significant impact on ecosystem service values in mining regions. By unraveling the nuanced relationship between land use dynamics and ESVs, our study not only fills the gap in the literature but also provides valuable insights for developing more effective ecosystem management strategies, ultimately advancing our understanding of ecosystem dynamics in human-impacted landscapes.https://www.mdpi.com/2072-4292/17/7/1139land use changeecosystem service valuesmining areaecological conservationGoogle Earth Engine (GEE) |
| spellingShingle | Shi Chen Jiwei Qin Shuning Dong Yixi Liu Pingping Sun Dongze Yao Xiaoyan Song Congcong Li Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification Remote Sensing land use change ecosystem service values mining area ecological conservation Google Earth Engine (GEE) |
| title | Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification |
| title_full | Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification |
| title_fullStr | Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification |
| title_full_unstemmed | Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification |
| title_short | Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification |
| title_sort | assessing the impact of land use changes on ecosystem service values in coal mining regions using google earth engine classification |
| topic | land use change ecosystem service values mining area ecological conservation Google Earth Engine (GEE) |
| url | https://www.mdpi.com/2072-4292/17/7/1139 |
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