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Spatial Agglomeration Level And Its Influencing Factors In Economic Development Zone Of Yellow River Basin Study

Posted on:2023-01-08Degree:MasterType:Thesis
Country:ChinaCandidate:X M MaFull Text:PDF
GTID:2569307025459374Subject:applied economics
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The Yellow River basin is an important ecological protection barrier and economic zone in China.As an important carrier of the economic development of the Yellow River basin,the economic development zone is an important force to promote the adjustment of industrial structure in the river basin.Studying the spatial agglomeration level of economic development zones and their influencing factors is of great significance for optimizing the spatial layout of development zones and realizing the ecological protection and high-quality development strategy of the Yellow River Basin.Based on the kernel density estimation method,this paper measures the spatial agglomeration level of economic development zones,analyzes the spatial autocorrelation of economic development zones,as well as the intensity and scale of agglomeration,and analyzes the influencing factors of spatial agglomeration in economic development zones by using the geographically and temporally weighted regression model.The main conclusions are as follows:(1)From the perspective of spatial agglomeration level measurement,the economic development zone in the Yellow River basin generally presents the spatial agglomeration characteristics of sparse in the East,dense in the South and sparse in the north,strong in the East and weak in the west,strong in the South and weak in the north,and the agglomeration level in the lower reaches is significantly higher than that in the middle and upper reaches,showing a multi-core agglomeration mode of one main and multiple auxiliary.(2)From the perspective of global spatial autocorrelation,the economic development zones show a significant positive correlation distribution in space and an agglomeration distribution pattern in the global space.From the perspective of local autocorrelation,high-high concentration areas are mainly distributed in the middle and lower reaches,low-low areas are mainly distributed in the middle and upper reaches,and low-high and highlow areas are mainly distributed in the middle reaches.(3)From the perspective of agglomeration intensity and agglomeration scale,the agglomeration intensity and agglomeration scale of economic development zones have very obvious differences in different regions,with multi-peak agglomeration characteristics in the upstream area and single peak agglomeration in the middle and downstream areas.(4)From the decomposition of the influencing factors of the spatial agglomeration level of economic development zones,all variables have significant temporal and spatial changes.From the perspective of time trend,the GDP,construction scale,per capita GDP,human resources,environmental protection and opening up of the economic development zone can promote the spatial agglomeration level of the development zone;Technological innovation and investment intensity have a negative impact on the spatial agglomeration of development zones.From the perspective of spatial distribution characteristics,GDP,opening-up and investment intensity of economic development zones play a significant role in the agglomeration of downstream development zones;The construction scale plays a significant role in the development zones of the whole basin,and human resources,technological innovation,environmental protection,and per capita GDP play a significant role in the agglomeration of middle and upper reaches of the development zones.Based on the above conclusions,suggestions are put forward to optimize the development of the Development Zone,such as promoting the rationalization of spatial layout,expanding the scale of employees,stimulating the vitality of technological innovation,strengthening environmental protection,and improving the level of opening to the outside world.
Keywords/Search Tags:Yellow River Basin, economic development zone, spatial agglomeration, geographically and temporally weighted regression
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