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 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.

Authors

Institutions

Publication Details

Journal
Geocarto International
Published
2025-01-27
DOI
https://doi.org/10.1080/10106049.2025.2451162
Citations
3
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
5.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating the impacts of large-scale opencast copper mining on vegetation productivity change in recent thirty years: a case study of Dexing Copper Mine

Hong Chi, Duan Huang, Hengkai Li, Zhiping Chen et al.
3 citations
Geocarto International
Remote Sensing in Agriculture
5.15
article

Evaluating the impacts of large-scale opencast copper mining on vegetation productivity change in recent thirty years: a case study of Dexing Copper Mine

Hong Chi, Duan Huang, Hengkai Li, Zhiping Chen, M. T. Liao
article en
3 citations

Abstract

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.

Geocarto InternationalVol. 40(1)
Chinese Academy of Sciences (CN), Ministry of Natural Resources (CN), China Geological Survey (CN), East China University of Technology (CN), Jiangxi Provincial Institute of Water Resources Planning and Design (CN), Jiangxi University of Science and Technology (CN)
Natural Science Foundation of Jiangxi Province, East China Institute of Technology, Yunnan Provincial Department of Education Science Research Fund Project, Open Research Fund Program of Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring
Openalex Percentile: Top 7%
Remote Sensing in Agriculture
5.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.