Urban Functional Area Identification And Spatial Composite Analysis Based On Multi-source Data

Along with the advancement of the urbanization process,various functional areas such as residential areas,industrial areas,public service areas,and commercial areas have been continuously formed in the process of urban development.Urban functional areas are an important part of urban planning.The study of urban functional area layout and mutual relations has important reference for grasping urban structure and formulating and using scientific and rational planning.Urban spatial planning research supported by traditional technologies is limited by the difficulty of obtaining source data,high cost and low precision.However,in the research scale of urban space,macroplanning lacks refined standards for urban space research.With the emergence of multisource open data such as POI,OSM,and GPS trajectory data,it can solve the problems that cannot be solved in traditional urban spatial planning research to a certain extent.Under such a status quo,the integration of multi-source open "big data" and traditional planning data has become a hot spot in current research spatial planning.On the basis of functional area recognition,from the perspective of multi-scale and multi-factors,Kernel Density analysis,image supervision and classification,spatial autocorrelation,location entropy analysis,average nearest neighbor distance,hot spot clustering and other methods were used to analyze the current spatial structure of yinchuan city.The composite of functional areas in the city.In this paper,using the block as a research unit,a suitable functional area identification system is constructed,and different eigenvalues are calculated as the basis for identifying the functional area.The functional area identification of the construction land in the three districts and two counties of Yinchuan City is divided into 9 A functional area,and the identification results are compared with the current status of land use and a planning adjustment strategy is proposed.The results show that the use of multi-source data for functional area identification can greatly compensate for the inadequacy of traditional planning data such as land use data that cannot accurately describe the internal functional distribution of the city.At the same time,based on the identification of functional areas,starting from multi-scale and multi-factors,using nuclear density analysis,image supervised classification,spatial autocorrelation,location entropy analysis,average nearest neighbor distance,hotspot analysis clustering,etc.The spatial structure of the city is analyzed.The research finds that(1)in the three different scales of municipal districts,streets and communities,the functional element dominant areas generally show the same distribution status under multiple scales,and the multiple functional elements in the same area in the urban area are well combined.(2)The areas with better functional elements are mainly concentrated in the range of 0-12 km from the center of the city,and the peripheral elements of the central city are single,which is too large.There are no multi-center development trends in cities,such as uneven internal and external use,unbalanced functional layout,and large differences in facilities and services.In the future optimization of spatial structure,it is necessary to adjust in time according to the development process and strengthen the construction of urban and rural integration in Yinchuan.