Combining Geographic Information System with Network Algorithm to Evaluate Accessibility of Urban Public Facilities Renewal

Abstract

The layout and renewal of urban public facilities mainly rely on traditional manual planning, lacking dynamic and systematic analysis. With the expansion of urban scale and the intensification of population mobility, public facilities’ distribution and service capacity face challenges, especially regarding information transmission and service efficiency. This paper applies an optimization method to evaluate the accessibility of urban public facilities renewal. First, the data of urban public facilities are collected and processed by GIS (Geographic Information System) technology. Based on the Dijkstra algorithm and spatial autocorrelation analysis, the blind spots and over-concentration problems in the layout of facilities are analyzed. By constructing a GIS-based network topology structure, combined with traffic flow and connectivity between public facilities, a weighted graph model is designed to optimize the data transmission path. Based on GIS technology, service blind spots are identified, and the location of facilities is optimized by combining center of gravity analysis with demand. At the same time, K-means clustering is combined to optimize service blind spots and shorten the average distance from residents to facilities. Dijkstra algorithm is then used to optimize the data transmission path between urban facilities. Finally, Monte Carlo simulation and sensitivity analysis are used to evaluate the impact of urban public facility renewal on data transmission efficiency and transmission delay. Experiments show that the average coverage rate of urban public facilities after optimization and evaluation reaches 84%, and the average packet loss rate in public facility data transmission is only 1.7%. This method provides strong support for future urban public facilities’ layout and renewal.