Examining spatial coordination of human-land-industry-service system from a regionalization approach: A case study of Beijing

Sustainable development requires a better understanding of the coupling relationship among population, urban land use, industry, and city services since they are closely related to the benefits of human beings. However, previous studies tend to focus on population and land use for urbanization-targeted insights without considering city services and industry development from a people-centered on the fine scale. This research aims to fill this gap by examining the spatial coordination of the human-land-industry-service system combining the coupling coordinated degree model and a regionalization approach with Beijing as a case study. Results show that about 3% area of Beijing is enjoying favorable coordination along with over 6% having moderate coordination, and sub-systems like human-land are experiencing better-coordinated development. Though the well-known monocentric structure of Beijing dominated by built-up expansion exists, sub-centers represented by Tongzhou and Changping rise to possibly alleviate the non-capital functions. In addition, Gini coefficients at 200-, 500-, 1000-, and 2000-meter scales decrease, and coarser resolutions present more continuous and smoother patterns. Three points concerning the unbalanced development, the scale effect, and the urbanization pattern of Beijing are further discussed. Our framework could be easily extended to explore interactions in other systems with the ability to consider both the fine details and the general spatial regionalization patterns. •A coupling analysis framework is proposed by combining coupling coordination degree model and regionalization approach.•Spatial coordination and hierarchical regionalization pattern of human-land-industry-service system of Beijing is examined.•Points concerning the unbalanced development, the scale effect, and the urbanization pattern of Beijing are discussed.•The proposed framework can explore both the fine details and the overall clustering patterns of any other systems.