Identification of Urban Functional Regions based POI data and the economic contribution index, a case study of Chongqing, China

Urban Functional Regions is an important basis for analyzing the urban spatial pattern and understanding urbanization progress. Accurately identifying the Urban Functional Regions is conducive to maximizing space efficiency. Point of interest (POI) data is strongly correlated with human activities and the function of urban areas. The identification of urban functional areas only by POI data points is challenging due to the differences in the numbers of different categories of POI data. In this study, we explored the economic contribution index and combined the analytic hierarchy process (AHP) and entropy method to modify the functional index model to identify the urban functional zones of Chongqing city, China. Results show that: 1) Single-type functional areas are dominantly distributed in the periphery of the study area. 2) In the dominant functional area, “finance-company” and “factory-company” POIs account for the highest proportion, and the two have a strong homogenization effect, which can better attract employees in spatial agglomeration. Overall, applying POI data and economic contribution index to modify the functional index model provides us with further solutions to urban functional region identification and improves the way of urban system analysis.