EconPapers    
Economics at your fingertips  
 

Exploring the Spatial Coupling Characteristics and Influence Mechanisms of Built Environment and Green Space Pattern: The Case of Shanghai

Rongxiang Chen, Zhiyuan Chen, Mingjing Xie, Rongrong Shi, Kaida Chen () and Shunhe Chen ()
Additional contact information
Rongxiang Chen: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Zhiyuan Chen: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Mingjing Xie: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Rongrong Shi: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Kaida Chen: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Shunhe Chen: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China

Sustainability, 2025, vol. 17, issue 15, 1-24

Abstract: Urban expansion will squeeze the green space system and cause ecological fragmentation. The question of how to expand cities more scientifically and build eco-cities has become an important topic of sustainable urban construction. This paper takes Shanghai as a research case. A deep neural network combined with an attention mechanism model measures the comprehensive level of the built environment and green space pattern of urbanization and quantitatively analyzes the coordinated relationship between the two using the coupled degree of coordination model. Subsequently, the K-Means clustering model was used for spatial clustering to determine the governance and construction directions for different spatial areas and was, finally, combined with the LightGBM model plus SHAP to analyze the importance and threshold effect of the indicators on the degree of coupled coordination. The results of the study show that (1) the core area of the city shows a high state of coordination, indicating that Shanghai has a better green space construction in the central city, but the periphery shows different imbalances; (2) three different kinds of areas are identified, and different governance measures as well as the direction of urbanization are proposed according to the characteristics of the different areas; and (3) this study finds that the structural indicators of the built environment, such as Average Compactness, Weighted Average Height, and Land Use Diversity, have a significant influence on the coupling coordination degree and have different response thresholds. The results of the study provide theoretical support for regional governance and suggestions for the direction of urban expansion for sustainable urbanization.

Keywords: machine learning; sustainable cities; spatial coupling characteristics; urban sprawl; spatial governance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/15/6828/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/15/6828/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:15:p:6828-:d:1711226

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-07-28
Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6828-:d:1711226