Evaluating the impacts of large-scale opencast copper mining on vegetation productivity change in recent thirty years: a case study of Dexing Copper Mine
Understanding the impact of mining on surrounding vegetation gross primary productivity (GPP) is crucial for the ecological management of mining areas. Using the simple non-iterative clustering (SNIC) and random forest (RF) methods, we mapped the Dexing Copper Mine (DCM) at a 30 m spatial resolution...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2451162 |
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| Summary: | Understanding the impact of mining on surrounding vegetation gross primary productivity (GPP) is crucial for the ecological management of mining areas. Using the simple non-iterative clustering (SNIC) and random forest (RF) methods, we mapped the Dexing Copper Mine (DCM) at a 30 m spatial resolution with Landsat data from 1991 to 2022. The vegetation photosynthesis model (VPM) was selected to simulate vegetation GPP. Sens slope test and Hurst exponent method jointly used to reveal the spatial-temporal evolution of vegetation GPP. Results showed: (1) SNIC+RF was more effective than RF alone. The mine area expanded from 5.23 km2 to 24.97 km2 due to deforestation; (2) The vegetation GPP in 53.17% of the areas has significantly increased. The GPP reduction areas are primarily around the open pit and the tailings; (3) Vegetation GPP loss due to land cover change was −2×1010 gC, −2.7×1010 gC, and −2.79×1010 gC for 1991-2000, 2000-2012, and 2012-2022. |
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| ISSN: | 1010-6049 1752-0762 |