Urban spatial dynamic modeling in transition
Hybrid, human-centric, and scalable futures
Bibliographic Data
| ID | 21408655 |
|---|---|
| Authors | Zipan Cai (0000-0001-7219-2222, Southeast University, corresponding author) |
| Year | 2026 |
| Publication date | 2026-05-14 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AMBIO (JOURNAL) |
| Journal identifiers | ISSN: 0044-7447 • E-ISSN: 1654-7209 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13280-026-02392-0 |
| PMID | 42133156 |
| OpenAlex | W7161136098 |
| Language | EN |
| References cited | 57 |
Urban spatial dynamic modeling (SDM) has long been used to anticipate land-use change, urban expansion, and infrastructure demand. Yet, despite increasing methodological sophistication, most applications remain oriented toward reproducing spatial patterns rather than supporting sustainability transitions. This perspective argues that SDM is at a turning point and outlines how it can evolve to address climate neutrality, resilience, and equity in both growing and shrinking cities. Five interlinked development pathways are proposed: (i) hybrid AI–theory models balancing predictive accuracy and interpretability; (ii) human-centric accessibility frameworks grounded in time geography; (iii) network-based resilience approaches drawing on graph theory and space syntax; (iv) semantic place functions enabled by vision–language foundation models; and (v) scalable architectures applicable across diverse data and governance contexts. Together, these pathways reposition SDM from a forecasting tool to a transition-support instrument, aligning it with planning support systems and enabling more sustainable and just urban futures
Corporate governance · Equity (law) · Futures contract · Graph · Scalability · Scenario planning · Spatial planning · Sustainability · Urban planning · 3D Modeling in Geospatial Applications · Land Use and Ecosystem Services · Urban Design and Spatial Analysis
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| Highly cited | No |
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