深圳市轨道交通车站与土地利用互动性研究OA北大核心CSTPCD

Urban rail transit and land use development mutually influence each other,and their coordinated development helps alleviate urban issues such as traffic congestion,which is one of the key aspects of sustainable urban development.Utilizing data in Shenzhen,including the building census data,land use data and rail transit station swipe data in 1999 and 2015,we perform a detailed analysis of the intrinsic relationship between rail transit station capacity and surrounding land use.This analysis covers various indicators such as development intensity,land use information entropy,station type and peak passenger flow during morning and evening.By introducing the"node-place"model,we construct an index system to evaluate the degree of coordination between rail transit stations and land use.The k-means clustering method is employed to classify the coordination status as subordinate,balanced and imbalanced states.The results indicate that with the development and construction of rail transit stations,the level of intensive land use around Shenzhen's rail transit stations has increased.There is a significant correlation between the passenger flow of stations and the surrounding land use indicators.All-day passenger flow is significantly positively correlated with the floor area ratio and commercial and office building area;morning peak passenger flow is significantly and positively correlated with residential building area and building density,and negatively correlated with the floor area ratio;while evening peak passenger flow is highly correlated with commercial building area and road network density.Overall,the coordinated development level between rail transit stations and their surrounding land use is relatively low.Station types predominantly fall into a subordinate state with low and balanced development of node and place values,while coordinated types are rare and mainly concentrated in the central area.Future efforts should focus on adopting targeted development strategies for imbalanced node areas to enhance their agglomeration effects and service levels.