A hierarchical spatial unit partitioning approach for fine-grained urban functional region identification
Abstract
Urban functional regions (UFRs) are formed and developed with human social actions and can reflect urban land use types. Appropriately identifying UFRs helps solve existing urban problems, optimize the spatial structure of cities, and provide a database for sustainable urban development. Most existing studies focus on developing novel methods and fusing multiple data sources, but neglect the impact of heterogeneous spatial units on UFR identification results. In this work, a hierarchical spatial unit partition approach was proposed to split the research area into many hierarchical units whilst considering the mixed degree of each unit. We further explored its capacity for identifying UFRs by integrating it with three widely used UFR identification methods. The results reveal that our proposed approach can correctly identify 10% more UFRs compared with the traditional grid-based method, showing the efficiency of our proposed approach for identifying UFRs at a finer scale. This work provides support for those who are engaged in urban planning and urban policymaking, promoting urban sustainable development.
