Research on Optimization of Urban Police Station Site Selection Based on Spatial Big Data
The increase in population density and the upgrading of urban functions have made it increasingly difficult to manage urban public safety.A spatial big data based model for the location selection of urban police stations is proposed to improve their management capabilities in urban public safety.This model utilizes urban interest point data to divide urban space into regions based on different functional features,and then optimizes the location of police stations according to the urban management weights of different regions.The results show that after optimization,the number of urban police stations can be reduced to 3,while the response time of police stations can still be maintained within 50 min,with a maximum response time of 48 min.The model constructed by the research can reduce the number of urban police stations based on the division of urban functional areas,while ensuring the management ability of police stations for urban public safety,effectively improving the utilization ability of urban space,and strengthening the urban public safety management responsibilities of police stations.
big datapolice stationsite selectionfunctional spaceurban planning
万方数据
维普
