| description abstract | In the old urban areas in China, due to the lack of comprehensive land use planning in the initial stages, urban functional areas have become complicated and chaotic. The primary objective of this study was to identify and gain a deeper understanding of the functional areas within an old city through the utilization of points of interest (POI). To achieve this, a POI query and filtering method were developed, leveraging the Baidu Map Application Programming Interface (API). Subsequently, a dedicated POI query program was designed to determine the functions of different areas. The effectiveness of the proposed method was demonstrated through an empirical application in the city of Fuzhou, China. Over 1 million POI were initially collected from 40 traffic analysis zones (TAZs) within the old city area of Fuzhou. After rigorous screening, 21,479 POI were identified and retained for further analysis. The following results were obtained: (1) the recognition accuracy of the functional area reaches 91.7%, effectively identifying the type of functional area; (2) the 40 TAZs in the old central districts of Fuzhou are divided into four types of functional areas (commercial, 8 areas; comprehensive, 24 areas; residential, 4 areas; and tourist attraction, 4 areas); (3) the commercial plots in the old city are mainly distributed on both sides of the city’s central axis, which serves as the primary commercial-based main axis responsible for urban transportation; and (4) a high proportion of the residential areas are distributed near schools, and the transportation facilities in these areas need to be improved. In summary, the method proposed in this study proves to be highly effective in analyzing the travel patterns of traffic communities. By providing essential data support for urban traffic planning and management, it significantly reduces the burden of the actual investigation workload. | |
