Evaluation of Vegetation Restoration Effectiveness in the Jvhugeng Mining Area of the Muli Coalfield Based on Sentinel-2 and Gaofen Data
To address the serious ecological problems caused by long-term mining in the Muli Coalfield, a three-year ecological restoration project was initiated in 2020. The Jvhugeng mining area was the largest and most ecologically damaged area in the Muli Coalfield. Vegetation restoration is the core of mine ecological restoration. Scientific evaluation of the vegetation restoration status in the Jvhugeng mining area is significant for comprehensively revealing ecological restoration effectiveness in the Muli Coalfield. Based on Sentinel-2’s spectral and temporal advantages and GF-1/GF-6’s high spatial resolution in detailed portrayal, fractional vegetation cover (FVC) and landscape pattern index were determined separately. Thus, the vegetation restoration effectiveness and spatiotemporal dynamics of the Jvhugeng mining area from 2020 to 2023 were evaluated in terms of structural and functional dimensions. The results show that, from 2020 to 2023, vegetation cover extent (varying from 8.77 km2 in 2020 to a peak of 17.93 km2 in 2022 and then decreasing to 13.48 km2 in 2023) and FVC (from 0.33 in 2020 to about 0.50 during 2021–2023) first increased sharply and then fluctuated. Vegetation regions with both high FVC and dominant landscape features also presented the characteristics of rapid expansion and then fluctuation. Vegetation restoration demonstrated significant effectiveness, with the natural ecological environment restored to some extent and remaining stable. Newly vegetated regions had high FVC and significant landscape pattern characteristics. However, vegetation cover expansion also led to further fragmentation and morphological complexity of vegetation landscape patterns in the study area. The results can provide a basis for quantitatively assessing ecological restoration effectiveness in the Jvhugeng mining area and even the Muli Coalfield. This can also provide a dual-source data synergy technical reference for dynamic monitoring and effective evaluation of vegetation restoration in other mining areas.
Authors
- Caiya Yue (ORCID: https://orcid.org/0000-0002-5017-4901)
- Zhonglin Ji (ORCID: https://orcid.org/0000-0002-9192-5783)
- Sen Jiao
- Junxing Liu (ORCID: https://orcid.org/0000-0002-6947-6627)
- Long Ju (ORCID: https://orcid.org/0000-0002-4691-1315)
- Lei Chen (ORCID: https://orcid.org/0000-0001-8341-0897)
- Yanxu Zhang (ORCID: https://orcid.org/0000-0002-4091-7142)
Institutions
- Liaocheng University (CN)
- China University of Mining and Technology (CN)
- China National Administration of Coal Geology (CN)
Publication Details
- Journal
- Land
- Published
- 2025-10-29
- DOI
- https://doi.org/10.3390/land14112151
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Key Research and Development Program of China