Using Food Delivery Data to Identify Urban -Rural Areas: A Case Study of Guangzhou, China

Abstract

It is an important task for planners and decision makers to determine whether a certain region is urban or rural since the accurate identification of these areas is of considerable significance to further study differences in urbanization development and balance contradictions between them. However, at present, there are problems of low efficiency and considerable subjectivity in the identification of urban and rural areas based on nighttime light data. Therefore, this study proposes a new method to identify urban and rural areas based on the differences between them. Taking Guangzhou as an example, this study simulated food delivery scenarios to identify urban and rural areas in Guangzhou. The findings indicated that using food delivery data to identify urban and rural areas is highly precise, with an accuracy rate of 92.4% and Kappa value of 0.79. This study provides a new method to identify urban and rural areas accurately and objectively, contributes to the study of urban-rural differences in urbanization and providing a feasible method for subsequent urban and rural planning.