Research And Application Of Urban Population Spatialization Simulation Based On Multi-source Data

People are the main body of urban social and economic activities,and population distribution is the most intuitive manifestation of human activities.With the continuous advancement of urbanization,excessive population growth and excessive clustering have become major challenges for urban management.Therefore,fine spatial simulation of the urban population can provide reliable data support for the city's scientific management and optimization of resource allocation.In recent years,technologies based on the Internet and location-based services(LBS)have developed rapidly,and a large amount of multi-source geospatial big data can be obtained from Internet websites or public service departments.These multi-source geospatial big data directly or indirectly reflect the distribution characteristics of urban populations,and provide new ideas for population spatialization research.In view of the lack of effective multi-source data fusion models in the current population space simulation research,the simulation spatial scale is too large,and the data such as building data and AOI data are not fully utilized.The paper uses POI data,road network data,building data,and Geospatial data such as social media data as data sources.A multi-source data fusion model for population spatialization simulation is proposed,and a database of multiple impact factors that affects the spatial distribution of the population is constructed.A random forest algorithm is introduced to create a multi-scale grid.This paper discusses the fine-grained distribution model of population space,and discusses the scale problem of population space simulation and its application in the assessment of urban public service facilities layout.The main work of the thesis includes the following aspects:(1)Correlation analysis of network multi-source geospatial data and population distribution.The degree of correlation between multi-source geospatial data and population spatial distribution was obtained through statistical data analysis.Among them,the population distribution has a very strong correlation with the distribution of health care services,commercial housing,government agencies,and social groups in POI data,0.762,0.723,0.634,respectively,the architecture of township residential building area density is second.At the same time,the population distribution has a strong correlation with the spatial distribution of Weibo users and We Chat easygo users.(2)Construction of urban multi-scale refined population spatial distribution model.Based on multi-source geospatial data and random forest algorithm,a multi-scale grid population spatial fine-grained distribution model was established,and the accuracy of the model was evaluated.The overall accuracy of the model is high,about 0.8004,and it has strong generalization ability.The population distribution influencing factors predicted by the model are basically consistent with the results of correlation analysis.The correlation coefficients of the multi-scale grid population predicted by the model and the actual population are higher than 0.7,the goodness of fit is higher than 0.5,and the overall simulation effect is good.At the same time,based on the analysis of the cause of the error,the relevant correction method can be used to effectively correct the simulation effect.(3)Taking the urban area of Zhengzhou as a research area,the spatial pattern of population distribution in the grid was studied and analyzed,and it was verified that the population distribution in the research area showed an obvious spatial autocorrelation relationship.Its global Moran index was as high as 0.880.The strong spatial agglomeration effect shows the spatial distribution pattern of population in the central urban area with high and high concentration and surrounding urban areas with low and low concentration.(4)Taking the study area as an example,the simulated population spatial data as the basis,and the educational resource layout evaluation as an example,the application analysis of the urban public service facility layout evaluation was performed to verify the reliability of the simulated population spatial distribution.