Effects of Mining on Urban Environmental Change: A Case Study of Panzhihua

Abstract

The environment supplies water, land, biological resources, and climate resources for people’s daily life and development, dramatically affecting the subsistence and development of human beings. Panzhihua City is a representative resource-based industrial city of southwestern China. The abundant mineral resources provide the material basis for the city’s development. However, while the overdevelopment of the past decades has provided the preconditions for its rapid economic growth, it has also inevitably had a huge impact on its environmental quality and land use structure. In this study, the landsat remote sensing images, terrain data, socio-economic data, and mining resources exploitation data of Panzhihua were used to extract the NDVI (Normalized Difference Vegetation Index), NDBSI (Normalized Difference Build and Soil Index) and LST (Land Surface Temperature) of the past 20 years at 5-year intervals. We normalized four indicators by Principal Component Analysis to derive a remote sensing ecological index of each factor and build the Remote Sensing-based Ecological Index evaluation model. This research quantified the changes in environmental quality in the past 20 years through the range method, showing that the environmental quality of Panzhihua City first declined and then increased slowly. This research also analyzed the influence of land use types, terrain, mining area, and socio-economy on the environmental quality of Panzhihua City by grey relational analysis and buffer analysis. It is found that with the influence of its unique topographical factors and economic aspects, the environmental quality of Panzhihua City changed to varying degrees. The results provide a reliable basis for the future environmental planning of Panzhihua City and a reference for the ecological restoration of mining areas with different mineral species accurately.

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

“…In addition, the superposition of RSEI with the vector boundaries of the mining area shows that RSEI can well characterize the boundary extent of the mine area, and coincides with the results of the remote sensing images. The trend of environmental quality in Panzhihua City in this study is basically consistent with the conclusion that the environment of Panzhihua City has been improving from 2001 to 2020 in Dai et al [94]. These show that RSEI has high applicability and objective accuracy as an indicator for assessing the environmental quality of mining cities.…”

The HANTS-fitted data in the vegetation growing season can improve RSEI accuracy in revealing the spatiotemporal patterns of ecological quality in Yuxi of China

“…All characteristics in this indicator are tightly linked to ecological quality and may be obtained through remote sensing technology alone. Therefore, it can monitor the ecological quality objectively, lowcostly, and quantitatively, and perform spatiotemporal visualization analysis (Dai et al, 2022). Several studies utilized the RSEI model to monitor ecological quality alterations in interior cities 16 , coastal island cities 17,18 , and plateau basins 19,20 .…”

The HANTS-fitted RSEI constructed in the vegetation growing season reveals the spatiotemporal patterns of ecological quality

“…Components of RSEI are not only strongly linked to ecological quality, but can also be derived exclusively from geospatial remote sensing technologies. Therefore, it can monitor the ecological quality objectively, low-costly, and quantitatively perform spatiotemporal visualization analysis 14 . Several studies utilized the RSEI model to monitor ecological quality alterations in interior cities 15 , coastal island cities 16 , 17 , and plateau basins 18 , 19 .…”