Analysis and Research of Urban Public Transport Network Based on ArcGIS

Abstract

With the continuous growth of urban populations and vehicles, traffic issues have become increasingly severe. The layout of public transport networks requires scientific planning, with evaluation analysis serving as the foundation for optimization. To address this, this study utilizes Python to obtain open-source data on Kunming's bus network. By employing spatial analysis and statistical methods in ArcGIS, we conducted evaluations at three levels—station, route, and network—based on established assessment criteria, providing a basis for public transport network planning in Kunming. The research employs Python code to acquire bus network data, overcoming challenges such as data accessibility and sample scarcity. The code is scalable to support nationwide urban studies. Results indicate: At the station level, 100% coverage rate within 500 meters and 89.47% coverage rate within 300 meters were achieved in central urban areas, rated as Level 1, indicating close proximity to stations and high service quality. However, the station density of approximately 6 per square kilometer was rated as Level 5, reflecting low station density. At the route level, the repetition coefficient of bus routes in central urban areas reached 3.37 (Level 3), suggesting excessive route duplication and reduced travel efficiency. The non-linear coefficient of bus routes was 1.53 (Level 3), further indicating inefficient travel patterns. At the network level, the bus network density in central urban areas stood at 6.01 km2/km2 (Level 1), demonstrating high accessibility to bus routes and superior service quality. In general, the public transport resource allocation in the built-up area of downtown Kunming is not high, the development of urban public transport is not coordinated with the regional social and economic development, and the regional public transport service level needs to be further improved.