In this study, two districts, Erdaojiang District and Dongchang District, in Tonghua City, Jilin Province, were evaluated for their geological environment carrying capacity. A total of 14 evaluation indicators were selected from the three aspects of the geological environment, ecological environment, and social environment to make it more comprehensive to evaluate the carrying capacity of the geological environment. Using the AHP and CRITIC methods, the subjective weight and objective weight of each evaluation index are obtained, and the combined weight is calculated by game theory. When combined with the GIS and combined weights, the distribution map of the geological environment carrying capacity is obtained, and it is classified into four grades: excellent, good, medium, and poor. A comprehensive evaluation of the carrying capacity of the geological environment is carried out. The following conclusions are drawn: the overall carrying capacity of the geological environment in the study area is good, and the carrying capacity of individual areas is poor. The comparative analysis of the good and poor areas provides a scientific basis for future environmental governance and urban planning and provides a scientific basis for geological disasters and mines.
The urbanization rate in China has been increasing in recent years, and along with the increasing intensity of human engineering activities, ecological and geological (eco-geological) degradation have become key factors impeding sustainable urban development. Taking the concentrated mineral exploitation area of Tonghua City as an example, the distribution of mines in the area is concentrated and the spatial heterogeneity is significant. This paper includes 14 evaluation indicators in three aspects: eco-geological environment background, anthropogenic and mining engineering activities, and environmental pollution. Then, based on game theory combined with ANP-CV (Analytic Network Process and Coefficient of Variation), two empowerment methods, GIS spatial calculation is used to evaluate the eco-geological environment quality (EEQ). The results showed that the EEQ was divided into grades I–V from high to low, with areas of 21.13%, 30.35%, 27.00%, 14.30%, and 7.22%, respectively; the EEQ of the Hun River basin has a high spatial autocorrelation and low EEQ, and the EEQ grade of mines was divided on this basis; the hot spot analysis is useful for determining the EEQ, as well as for allocating mine restoration resources in a sensible manner. Finally, we propose countermeasures to improve EEQ, and this study can provide a scientific basis for ecological construction and geological environmental protection in Tonghua City.
Taking Erdaojiang and Dongchang District of Tonghua City, Jilin Province as examples, this paper studies the ecological environment restoration and governance model of their mining areas. In this paper, the vegetation cover (NDVI) data in the past ten years were selected from the study area. The Theil–Sen median and Mann–Kendall (MK) methods were used to analyze the time series of NDVI, and the vegetation cover change trend map of the study area was obtained. Then, the land use data of the study area for 4 years were selected, and the transfer matrix method was used to analyze the land use conversion between the years. Finally, according to the characteristics of the distribution of mines in the study area, for the mining area in different natural geographical locations, it was concluded that the restoration of cultivated land and the restoration of forest land and ecological reconstruction were adopted. Among them, the restoration of forest land includes natural restoration and artificial intervention.
This study evaluated the eco-geological environment quality of Hunjiang District, Baishan City, Jilin Province. Fifteen indicators were selected from geological, ecological, and social aspects to make the eco-geological environmental quality assessment more comprehensive. On the basis of improved game theory, two weighting methods of FAHP-CV (Fuzzy Analytic Hierarchy Process and Coefficient of Variation) were used to calculate the weight, and finally ArcGIS was used to intuitively understand the eco-geological environment quality of the study area. According to a threshold value, the eco-geological environment quality of the study area was divided into five types: better, good, medium, bad, and worse, and the results show that the overall eco-geological environment quality of the study area is in the middle and upper levels. The eco-geological environment quality of a small part of the area is poor. The classification of the eco-geological environment quality of Hunjiang District provides a scientific basis for the establishment of reasonable eco-geological environment protection and urban planning in the future.
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