Comparative Study On The Economic Impact Of High Speed Railway On Urban Agglomeration Based On GWR

With the opening of the "Beijing Tianjin Intercity Railway" in 2008,China’s high-speed railway has entered a period of rapid development.By the end of 2020,five provinces,namely Fujian,Anhui,Jiangsu,Jiangxi,and Hebei,had achieved the goal of "connecting cities with high-speed rail".At the same time,the urban agglomeration strategy has been elevated to a national strategy,and China has successively planned 19 national level urban agglomerations.As the most convenient mode of transportation within urban agglomerations,high-speed rail plays an important role in promoting economic integration and regional coordinated development of urban agglomerations.However,due to differences in geographical location,economic foundation,macro policies,and other aspects,the economic effects of high-speed rail in different regions are also different.Therefore,exploring the differences in the impact of high-speed rail on different urban agglomerations has certain reference and reference significance for the subsequent construction and economic development of high-speed rail in urban agglomerations.This thesis takes the Beijing Tianjin Hebei and Yangtze River Delta urban agglomerations where highspeed railway developed earlier as examples,and analyzes the impact of high-speed railway on the two urban agglomerations from reachability,economic spatial structure,economic growth factors and other aspects,and then puts forward countermeasures and suggestions for the development of urban agglomerations.This thesis first analyzes the reachability of two urban agglomerations before and after the opening of high-speed rail.The shortest travel time,weighted average travel time and reachability coefficient are selected to calculate the reachability evolution of each city,and the spatial interpolation method in Arc GIS is used to visually display the reachability of urban agglomeration.Secondly,in order to study the impact of high-speed rail on the spatial structure of urban agglomeration,the Gravity model is used to calculate the economic connection intensity,economic membership and economic potential value between the cities of the two urban agglomeration,and compare the differences in the impact of high-speed rail on the economic spatial structure of urban agglomeration.Finally,the core objective of this article is to study the impact of high-speed railways on the economic scale and growth factors of urban agglomerations.A global regression model and a geographically weighted regression model are established for this,and the spatial statistical tools in Arc GIS are used to calculate the regression models of the two urban agglomerations and visualize the calculation results.The results show that the impact of high-speed railway on different economic activities has spatial heterogeneity,and GWR model can better explain the difference of economic impact of high-speed railway on different urban agglomerations.The comprehensive results show that the high-speed railway network can greatly improve the overall reachability of the urban agglomeration,but the improvement effect of reachability is different in different urban agglomerations and cities.On the basis of the improvement of reachability,the economic spatial structure of urban agglomeration has undergone significant changes.The impact of high-speed rail on the internal economic links of urban agglomeration has two effects: "agglomeration" and "diffusion".The Beijing Tianjin Hebei urban agglomeration is more characterized by "agglomeration effect",while the Yangtze River Delta urban agglomeration has a significant "diffusion effect".At the same time,there are significant differences in the impact of high-speed railways on various economic growth factors in different urban agglomerations.This difference was compared from four aspects of population,urbanization,investment,and income in urban agglomerations,providing reference for the subsequent high-speed rail construction and economic development of urban agglomerations.