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Comprehensive Carrying Capacity Evaluation And Spatial-temporal Differentiation Of Mineral Resource-based Cities

Posted on:2021-04-30Degree:MasterType:Thesis
Country:ChinaCandidate:Y H ShiFull Text:PDF
GTID:2439330629451305Subject:Management Science and Engineering
Abstract/Summary:
Mineral resources are important sources of processing raw materials and energy,and the resource extraction industry has greatly promoted the level of economic and social development in production areas.However,with the large-scale and in-depth exploitation of mineral resources,resource-based cities have exposed many crises,such as insufficient reserves of mineral resources,labor outflow,difficulty in extracting existing resources,and difficulties in transition.Cities suffer severe economic,social and environmental crises.Therefore,it is urgent to accurately identify the level of urban carrying capacity,and to promote the sustainable development of cities is urgent.At present,the evaluation objects of the carrying capacity are mainly focused on coastal cities,tourism areas,agricultural areas,etc.,Mineral resources-based cities have received less attention.With the help of this research,not only can we analyze the carrying capacity of different cities and the shortcomings that limit urban development,but it can also help government departments take targeted measures to improve the sustainable development of cities and urban agglomerations.First,this paper clarifies the composition of a mineral resource-based city system and defines the scientific connotation of comprehensive carrying capacity.Combine the PSR model to explore the response mechanism of the comprehensive carrying capacity of mineral resource-based cities,and then establish an initial index system including five sub-dimensions of economy,society,resources,environmental subsystems and synergy,then propose a novel R-type clustering analysis-technique for order preference by similarity to ideal solution-rank sum ratio-exploratory spatial data analysis(RCA-TOPSIS-RSR-ESDA)methodology.Then,we selected 41 representative cities as objects,and calculated the mineral resource-based cities comprehensive carrying capacity index(MRCCCI).In order to identify the short planks of the city’s development,this study calculate the resource carrying capacity index(REI),social carrying capacity index(SOI),environmental carrying capacity index(ENI),economic carrying capacity index(ECI),and synergy degree index(SDI).And use the sub-dimension ranking to measure the balance of urban development.On this basis,the classification of mineral resource-based cities based on comprehensive carrying capacity and sub-dimensional equilibrium is realized.Finally,in order to reveal the spatial correlation patterns between cities with different carrying capacity levels,the ESDA method was used to visually describe the spatial distribution characteristics of carrying capacity.The conclusions show that:(1)from the overall perspective,there are differences in the comprehensive carrying capacity of different cities.There are eight cities whose MRCCCI scores are always higher,including TY,DQ,AS,etc.While there are eight cities whose MRCCCI scores are always lower,including HD,HB,HN,etc.(2)From the perspective of sub-dimensional equilibrium,there is a large difference in the sub-dimensional equilibrium among different cities,and most cities show poorer equilibrium.(3)From the classification results,the constraints of the comprehensive carrying capacity differed in different cities.Even in cities with the same comprehensive carrying capacity,their short planks were significantly different.(4)From the perspective of spatial and temporal distribution,from 2010 to 2016,there was a strong spatial autocorrelation in the comprehensive carrying capacity of China’s mineral resource-based cities,and there were obvious regional characteristics in the significant spatial agglomeration areas.This thesis has 16 figures,12 tables and 117 references.
Keywords/Search Tags:mineral resource-based cities, comprehensive carrying capacities, synergy, composite index, spatio-temporal analysis
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