Exploring the growth pattern of urban agglomeration in the terminal urbanization stage by integrating inertial driving factors, spatial development strategy, and urbanization cycle

Abstract

Simulating land use/cover change (LUCC) caused by urbanization is always one of the most important aspects in city’s sustainable development. Previous research mainly simulated urban growth ignoring the periodical characteristics of urbanization cycle, which cannot well meet the needs of optimizing the relationship between urban, agriculture and ecological space. We developed a framework to explore the stable pattern in the terminal urbanization stage including the following parts: bottom-up conversion probability was mainly estimated from inertial driving factors, subregional top-down expansion trends were discovered from spatial development strategy and urbanization cycle represented as the constrained S-curves, and the above transformation rules were integrated into EasyCA to obtain urban growth pattern. To verify the model’s practicality, Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was selected as a case study. Results demonstrate that (1) Planning strategy can greatly reshape the growth pattern particularly in large areas; (2) Subregional constrained S-curves can predict urban quantity reasonably considering the characteristics of urbanization cycle; (3) The coupled model can obtain referable simulation pattern of urban agglomeration in the terminal urbanization stage. It can provide an innovative tool for making decision and has great significance in city’s sustainable development.

Keywords

• Urban agglomeration
• Urban growth
• Urbananization cycle
• Cellular automata
• City’s sustainable development