Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration
Vegetation resilience is crucial for understanding the self-repair and adaptive capacity of regional ecosystems. Opencast coal mine dumps, typical targets for ecological restoration, exhibit highly unstable vegetation ecosystems after restoration, making them prone to state shifts. However, existing...
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Elsevier
2025-07-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225002936 |
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| author | Hui Wang Chengye Zhang Yaxin Ding Feiyue Li Wanxi Liu Yan Ma Yingjie Guo Bikram Banerjee Jun Li |
| author_facet | Hui Wang Chengye Zhang Yaxin Ding Feiyue Li Wanxi Liu Yan Ma Yingjie Guo Bikram Banerjee Jun Li |
| author_sort | Hui Wang |
| collection | DOAJ |
| description | Vegetation resilience is crucial for understanding the self-repair and adaptive capacity of regional ecosystems. Opencast coal mine dumps, typical targets for ecological restoration, exhibit highly unstable vegetation ecosystems after restoration, making them prone to state shifts. However, existing studies have limitations in capturing vegetation resilience characteristics and its climatic driving mechanisms. This study addresses these deficiencies by focusing on the Pingzhuang West Opencast Coal Mine dumps, utilizing Critical Slowing Down (CSD) theory and long-term Landsat remote sensing data from 2008 to 2024. We propose ’MultiRes’, a pixel-level (30 m) method to calculate vegetation resilience. Unlike traditional fixed-window approaches, MultiRes offers adaptive window sizes with a wide range of stability. We analyzed the spatiotemporal dynamics of vegetation resilience after restoration, evaluated the effectiveness of vegetation restoration, and quantitatively assessed the impact of key climatic drivers across different phases. Results reveal that: (1) After restoration, vegetation resilience at each dump experienced three phases: initial enhancement, decline, and renewed enhancement. (2) Vegetation resilience improved significantly compared to the initial fragile ecosystem, with over 88 % of the area showing improvement, especially at Taipingdi, where the enhancement rate reached 99.85 %. (3) The influence of key climatic drivers remained consistent within each dump across all phases, particularly in the first and third phases. Areas dominated by a single climatic driver generally showed more significant changes than those influenced by combined drivers. These findings demonstrate that vegetation resilience captures stage-specific ecological patterns that NDVI alone cannot detect, thereby supporting adaptive restoration and climate-informed management in mining environments. |
| format | Article |
| id | doaj-art-435b4a8d8cda48889efbec0b5c0b71c4 |
| institution | DOAJ |
| issn | 1569-8432 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-435b4a8d8cda48889efbec0b5c0b71c42025-08-20T03:22:11ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-07-0114110464610.1016/j.jag.2025.104646Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restorationHui Wang0Chengye Zhang1Yaxin Ding2Feiyue Li3Wanxi Liu4Yan Ma5Yingjie Guo6Bikram Banerjee7Jun Li8College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China; China Coal Green Energy Technology Co., Ltd., Beijing 100871, ChinaCollege of Urban and Environmental Sciences, Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, ChinaNeimenggu pingzhuang Coal Industry (Group) Co., Ltd., Chifeng City, Inner Mongolia Autonomous Region, Chifeng 024000, ChinaSchool of Surveying and Built Environment, University of Southern Queensland, Toowoomba, Queensland 4350, AustraliaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China; Corresponding author at: No.11 Xueyuan Road Street, Haidian District, Beijing, China.Vegetation resilience is crucial for understanding the self-repair and adaptive capacity of regional ecosystems. Opencast coal mine dumps, typical targets for ecological restoration, exhibit highly unstable vegetation ecosystems after restoration, making them prone to state shifts. However, existing studies have limitations in capturing vegetation resilience characteristics and its climatic driving mechanisms. This study addresses these deficiencies by focusing on the Pingzhuang West Opencast Coal Mine dumps, utilizing Critical Slowing Down (CSD) theory and long-term Landsat remote sensing data from 2008 to 2024. We propose ’MultiRes’, a pixel-level (30 m) method to calculate vegetation resilience. Unlike traditional fixed-window approaches, MultiRes offers adaptive window sizes with a wide range of stability. We analyzed the spatiotemporal dynamics of vegetation resilience after restoration, evaluated the effectiveness of vegetation restoration, and quantitatively assessed the impact of key climatic drivers across different phases. Results reveal that: (1) After restoration, vegetation resilience at each dump experienced three phases: initial enhancement, decline, and renewed enhancement. (2) Vegetation resilience improved significantly compared to the initial fragile ecosystem, with over 88 % of the area showing improvement, especially at Taipingdi, where the enhancement rate reached 99.85 %. (3) The influence of key climatic drivers remained consistent within each dump across all phases, particularly in the first and third phases. Areas dominated by a single climatic driver generally showed more significant changes than those influenced by combined drivers. These findings demonstrate that vegetation resilience captures stage-specific ecological patterns that NDVI alone cannot detect, thereby supporting adaptive restoration and climate-informed management in mining environments.http://www.sciencedirect.com/science/article/pii/S1569843225002936Mine vegetation resilienceCritical Slowing Down theoryAC(1)Remote sensingOpencast coal mine dump |
| spellingShingle | Hui Wang Chengye Zhang Yaxin Ding Feiyue Li Wanxi Liu Yan Ma Yingjie Guo Bikram Banerjee Jun Li Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration International Journal of Applied Earth Observations and Geoinformation Mine vegetation resilience Critical Slowing Down theory AC(1) Remote sensing Opencast coal mine dump |
| title | Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration |
| title_full | Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration |
| title_fullStr | Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration |
| title_full_unstemmed | Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration |
| title_short | Spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration |
| title_sort | spatiotemporal dynamics and key climatic influences on vegetation resilience in opencast coal mine dumps after restoration |
| topic | Mine vegetation resilience Critical Slowing Down theory AC(1) Remote sensing Opencast coal mine dump |
| url | http://www.sciencedirect.com/science/article/pii/S1569843225002936 |
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