A constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data

Studies on urban–rural fringes, which represent regions facing various urbanization problems caused by rapid expansion, have steadily increased in recent years. However, problems persist in the quantitative delimitation of such regions. In this study, we propose an approach that combines spatial continuous wavelet transform with a constraint-based boundary recognition method to detect the urban–rural fringes of polycentric cities based on data from multiple sources. According to the characteristics of urban geospatial mutability, we used the proposed approach not only to delimitate the fringe areas of two cities, Jiangyin and Zhangjiagang, but also to identify their main and vice city centers, towns, and rural hinterlands. Based on the characteristics of landscape fragmentation, diversity, and complexity in the urban–rural fringes, patch density and Shannon’s diversity index obtained in our study were compared with the results of other methods. This comparison confirmed that the proposed approach performs better and its effectiveness is due to the construction of a comprehensive urbanization index and the design of a constraint-based boundary recognition method. Thus, the proposed approach is suitable for extracting the urban–rural fringe of polycentric cities and can be applied to future urban spatial analysis, planning, and management.