Bridging Subjective and Objective Dimensions of Resilience: A Space Syntax Approach to Analyzing Urban Public Spaces
Abstract
1. Introduction
2. Literature Review and Conceptual Framework
2.1. Literature Review
2.1.1. The Connotation of PSR
2.1.2. Measuring PSR
2.2. Conceptual Framework
3. Methods and Materials
3.1. Study Area
3.2. Data Collection
3.3. Methods
3.3.1. Integration and Spatial Accessibility, Robustness
3.3.2. Connectivity and Spatial Permeability, Redundancy
3.3.3. Comprehensibility and Spatial Cognition, Safety
4. Results and Analysis
4.1. Robustness of Space
4.2. Redundancy of Space
4.3. Safety of Space
4.4. Comprehensive Resilience of Urban Public Space
5. Discussion
5.1. Validation of Space Syntax Measurement Results
5.1.1. Verification of Spatial Robustness, Redundancy and Safety
5.1.2. Verification of Comprehensive Urban PSR
5.2. Theoretical and Practical Implications
- Enhancing the Accessibility and Robustness of Public Spaces
- Systematic Optimization of Public Space Layout to Enhance Redundancy
- Sorting Out the Yuzhong Peninsula Street Network to Ensure Safety
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Wang, S.F.; Li, Z.M. New Normal Inspired by the COVID-19 Pandemic: Spatial Resilience and Planning Response. J. Hum. Settl. West China 2020, 35, 18–24. (In Chinese) [Google Scholar] [CrossRef]
- Elewa, A.K.A. Flexible Public Spaces through Spatial Urban Interventions, Towards Resilient Cities. Eur. J. Sustain. Dev. 2019, 8, 152. [Google Scholar] [CrossRef]
- Allan, P.; Bryant, M.; Wirsching, C.; Garcia, D.; Teresa Rodriguez, M. The influence of urban morphology on the resilience of cities following an earthquake. J. Urban Des. 2013, 18, 242–262. [Google Scholar] [CrossRef]
- Li, X.; Li, L.; Lin, M.; Jim, C.Y. Research on Risk and Resilience Evaluation of Urban Underground Public Space. Inter-Natl. J. Environ. Res. Public Health 2022, 19, 15897. [Google Scholar] [CrossRef]
- Lu, Y.; Zhai, G.; Zhou, S.; Shi, Y. Risk reduction through urban spatial resilience: A theoretical framework. Hum. Ecol. Risk Assess. Int. J. 2020, 27, 921–937. [Google Scholar] [CrossRef]
- French, E.L.; Jeff Birchall, S.; Landman, K.; Brown, R.D. Designing public open space to support seismic resilience: A systematic review. Int. J. Disaster Risk Reduct. 2019, 34, 1–10. [Google Scholar] [CrossRef]
- Suleimany, M.; Mokhtarzadeh, S.; Sharifi, A. Community resilience to pandemics: An assessment framework developed based on the review of COVID-19 literature. Int. J. Disaster Risk Reduct. 2022, 80, 103248. [Google Scholar] [CrossRef]
- Huizenga, S.; Oldenhof, L.; Bovenkamp, H.V.D.; Bal, R. Governing the resilient city: An empirical analysis of governing techniques. Cities 2023, 135, 104237. [Google Scholar] [CrossRef]
- Jones, L.; D’Errico, M. Whose resilience matters? Like-for-like comparison of objective and subjective evaluations of resilience. World Dev. 2019, 124, 104632. [Google Scholar] [CrossRef]
- Ensor, J.E.; Mohan, T.; Forrester, J.; Khisa, U.K.; Karim, T.; Howley, P. Opening space for equity and justice in resilience: A subjective approach to household resilience assessment. Glob. Environ. Change 2021, 68, 102251. [Google Scholar] [CrossRef]
- Li, T.Y. New progress in research on resilient cities. Urban Plan. Int. 2017, 32, 15–25. (In Chinese) [Google Scholar] [CrossRef]
- Lu, Y.W.; Zhai, G.F. Research Progress and Perspectives on the Theory and Practice of Urban Spatial Resilience. Shanghai Urban Plan. Rev. 2022, 6, 1–7. (In Chinese) [Google Scholar]
- NystrÖm, M.; Folke, C. Spatial resilience of coral reefs. Ecosystems 2001, 4, 406–417. [Google Scholar] [CrossRef]
- Cumming, G.S. A Theoretical Framework for the Analysis of Spatial Resilience; Springer: Dordrecht, The Netherlands, 2011; pp. 35–66. [Google Scholar]
- Zhou, Q.; Zheng, Y. Research on the spatial layout optimization strategy of Huaihe Road Commercial Block in Hefei city based on space syntax theory. Front. Comput. Neurosci. 2023, 16, 1084279. [Google Scholar] [CrossRef]
- Kim, J.; Park, S.; Kim, M. Safety map: Disaster management road network for urban resilience. Sustain. Cities Soc. 2023, 96, 104650. [Google Scholar] [CrossRef]
- Allen, C.R.; Angeler, D.G.; Cumming, G.S.; Folke, C.; Twidwell, D.; Uden, D.R. Quantifying spatial resilience. J. Appl. Ecol. 2016, 53, 625–635. [Google Scholar] [CrossRef]
- Wang, L.; Han, X.; He, J.; Jung, T. Measuring residents’ perceptions of city streets to inform better street planning through deep learning and space syntax. ISPRS J. Photogramm. Remote Sens. 2022, 190, 215–230. [Google Scholar] [CrossRef]
- Wen, H.; Ye, Y.; Zhang, L. Optimizing road networks in underdeveloped regions for improving comprehensive efficiency integrated by accessibility, vulnerability and socioeconomic interaction. Reliab. Eng. Syst. Saf. 2024, 243, 109848. [Google Scholar] [CrossRef]
- Akopov, A.S.; Beklaryan, L.A. Evolutionary Synthesis of High-Capacity Reconfigurable Multilayer Road Networks Using a Multiagent Hybrid Clustering-Assisted Genetic Algorithm. IEEE Access 2025, 13, 53448–53474. [Google Scholar] [CrossRef]
- Penn, A. Space Syntax and Spatial Cognition: Or Why the Axial Line? Environ. Behav. 2003, 35, 30–65. [Google Scholar] [CrossRef]
- Esposito, D.; Santoro, S.; Camarda, D. Agent-Based Analysis of Urban Spaces Using Space Syntax and Spatial Cognition Approaches: A Case Study in Bari, Italy. Sustainability 2020, 12, 4625. [Google Scholar] [CrossRef]
- Fan, P.Y.; Chun, K.P.; Mijic, A.; Tan, M.L.; Liu, M.S.; Yetemen, O. A framework to evaluate the accessibility, visibility, and intelligibility of green-blue spaces (GBSs) related to pedestrian movement. Urban For. Urban Green. 2022, 69, 127494. [Google Scholar] [CrossRef]
- Xu, Y.; Rollo, J.; Esteban, Y. Evaluating Experiential Qualities of Historical Streets in Nanxun Canal Town through a Space Syntax Approach. Buildings 2021, 11, 544. [Google Scholar] [CrossRef]
- Han, R.; Liu, D.; Zhu, G.; Li, L. A Comparative Study on Planning Patterns of Industrial Bases in Northeast China Based on Spatial Syntax. Sustainability 2022, 14, 1041. [Google Scholar] [CrossRef]
- Alawi, M.; Chu, D.; Hammad, S. Resilience of Public Open Spaces to Earthquakes: A Case Study of Chongqing, China. Sustainability 2023, 15, 1092. [Google Scholar] [CrossRef]
- Chathuranganee Jayakody, R.R.J.; Amaratunga, D. Guiding factors for planning public open spaces to enhance coastal cities’ disaster resilience to tsunamis. Int. J. Disaster Resil. Built Environ. 2020, 12, 471–483. [Google Scholar] [CrossRef]
- Choi, H.S.; Bruyns, G.; Zhang, W.; Cheng, T.; Sharma, S. Spatial Cognition and Three-Dimensional Vertical Urban Design Guidelines—Cognitive Measurement and Modelling for Human Centre Design. Urban Sci. 2023, 7, 125. [Google Scholar] [CrossRef]
- Hillier, B. Cities as movement economies. URBAN Des. Int. 1996, 1, 41–60. [Google Scholar] [CrossRef]
- Mckenzie, G.; Janowicz, K.; Adams, B. A weighted multi-attribute method for matching user-generated Points of Interest. Cartogr. Geogr. Inf. Sci. 2014, 41, 125–137. [Google Scholar] [CrossRef]
- Qanazi, S.; Hijazi, I.H.; Shahrour, I.; Meouche, R.E. Exploring Urban Service Location Suitability: Mapping Social Behavior Dynamics with Space Syntax Theory. Land 2024, 13, 609. [Google Scholar] [CrossRef]
- Soltani, A.; Javadpoor, M.; Shams, F.; Mehdizadeh, M. Street network morphology and active mobility to school: Applying space syntax methodology in Shiraz, Iran. J. Transp. Health 2022, 27, 101493. [Google Scholar] [CrossRef]
- Wang, Z.T.; Wu, J.F.; Guo, X.D. Study on Optimization of Functional Area Layout of Disaster Prevention Shelters. J. Catastrophology 2023, 38, 127–133. [Google Scholar]
- Gangwal, U.; Siders, A.R.; Horney, J.; Michael, H.A.; Dong, S. Critical facility accessibility and road criticality assessment considering flood-induced partial failure. Sustain. Resilient Infrastruct. 2022, 8 (Suppl. S1), 337–355. [Google Scholar] [CrossRef]
- Nel, D.; du Plessis, C.; Landman, K. Planning for dynamic cities: Introducing a framework to understand urban change from a complex adaptive systems approach. Int. Plan. Stud. 2018, 23, 250–263. [Google Scholar] [CrossRef]
- Lyu, Y.; Malek, M.I.A.; Ja’afar, N.H.; Sima, Y.; Han, Z.; Liu, Z. Unveiling the potential of space syntax approach for revitalizing historic urban areas: A case study of Yushan Historic District, China. Front. Archit. Re-Search 2023, 12, 1144–1156. [Google Scholar] [CrossRef]
- Chu, D.Z.; Wang, Y.H. Boundary, Link and Security: Exploring the Optimization Strategies for Transport Space System of Peninsula Headland Area in Urban Design. Archit. J. 2022, 647, 86–93. (In Chinese) [Google Scholar] [CrossRef]
- Li, Y.Y.; Peng, Y.; Li, Z. Research on Optimization of Disaster-prevention Space of High-density Old City Based on Crowd Activity Distribution: A Case Study of Yuzhong Peninsula of Chongqing. New Archit. 2021, 1, 41–46. (In Chinese) [Google Scholar] [CrossRef]
Data Type | Data Content | Data Source |
---|---|---|
Vector data | Road; Administrative boundaries | OSM website 2023 (https://www.openstreetmap.org, accessed on 9 December 2024); 1:250,000 national basic geodatabases (https://www.webmap.cn, accessed on 12 December 2024) |
POI data | Public space POI data | OSM website 2022 (https://www.openstreetmap.org, accessed on 9 December 2024) |
Parametric Indicators | Calculation Formula | Syntactic Parameter Paraphrasing | Resilience in Public Spaces | Analyze Features |
---|---|---|---|---|
Global Integration Ii Local Integration G | , G=, where, i denotes the ith space; Ii denotes the global Integration of the ith space; n denotes the total number of axes of the public space structural system; Dn is a standardized parameter; Dm is the average depth. the equations for Dn and Dm are: where, i denotes the ith space; j denotes the jth space; dij denotes the depth and represents the shortest topological distance between the ith and jth points of the connection. | The degree of integration indicates the degree of aggregation or dispersion of a node from other nodes. The global integration degree reflects the ease of reaching each other between the nodes in the overall space, while the local integration degree represents the relationship between a certain space node and other space nodes within a few steps of topological distance. The higher the degree of integration, the higher the accessibility between system nodes. | This metric indicates the capacity of a spatial node to be accessed by other nodes within the overarching system topology. Locations with higher integration levels tend to attract more individuals and are utilized to evaluate whether evacuees can swiftly reach a safe location, thereby illustrating greater robustness and the ability to endure disasters. | Accessibility Robustness |
Connectivity Ci | Ci = k i denotes the ith space; Ci denotes the connectivity of the ith space; and k denotes the number of spaces directly connected to the i space. | This metric indicates the number of spatial connections within the system node space. A system node with more connections to other nodes will have a higher connection value, resulting in improved spatial connectivity within the system. | This indicates the number of nodes connected to a spatial node. A higher number of connections enhances the permeability of a space within the system. Resilient public spaces must exhibit permeability, which implies that they should be accessible to the public and possess both physical and functional connections to urban environments. | Permeability Redundancy |
Comprehensibility R2 | where Ci, are the connectivity and its average value; Ii, are the global integration and its average value. | Indicates the relationship between local space and overall space, and the difficulty of perceiving the overall spatial structure from the local space. | The comprehensibility of a space significantly enhances individuals’ ability to perceive and understand it. A comprehensible environment facilitates navigation, thereby aiding people in finding their way. As the clarity of a space increases, so too does the sense of safety it provides; in contrast, a confusing space tends to evoke feelings of insecurity. | Degree of Awareness Security |
Public Space | Robustness | Redundancy | Safety | Comprehensive Resilience Level |
---|---|---|---|---|
4 Square 2 | + | + | − | High |
7 People’s Park | + | + | − | High |
16 Square 1 | + | + | − | High |
15 Tongyuanmen City Wall Ruins Eco-Park | + | + | − | High |
28 Renhe Street Elementary School | + | + | − | High |
31 Jialing River Waterfront Trail | + | + | − | High |
2 Raffles City | + | + | − | High |
10 Fudan Middle School Kai Spiral Road Campus | + | + | − | High |
17 Experimental schools | + | + | − | High |
21 Bashu Middle School | + | + | − | High |
8 Culture Street Middle School | + | − | − | Medium |
6 Baixiang Street Center Ecological Park | + | − | − | Medium |
12 Mingguang Square | + | − | − | Medium |
29 People Street Community Park | + | − | − | Medium |
5 East Watergate Elementary School | + | − | − | Medium |
18 Zhongshan Primary School | + | + | − | Medium |
33 Seikyo High School | − | + | − | Medium |
1 Chaotianmen Square | − | + | − | Medium |
23 Bashu Middle School | − | + | − | Medium |
11 Riverside Park | − | + | − | Medium |
30 People’s Square | − | + | − | Medium |
27 Palace of Culture Square | − | + | − | Medium |
3 Cotton Street Sports, Culture and Ecological Park | − | + | − | Medium |
32 Zengjiayan Bridge South Qiaotou Square | − | − | − | Low |
9 Datang Square | − | − | − | Low |
19 Outside Fudan Middle School Chinese language school | − | − | − | Low |
25 Zou Rong Park | − | − | − | Low |
13 Xinglin Middle School | − | − | − | Low |
24 Parking lots | − | − | − | Low |
20 Loquat Hill Park | − | − | − | Low |
22 Bashu Primary School Zhangjia Garden Campus | − | − | − | Low |
26 Coral Park | − | − | − | Low |
14 Ren’ai Wilderness Eco-Park | − | − | − | Low |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, Y.; Wang, M.; Wang, B.; Liang, Y. Bridging Subjective and Objective Dimensions of Resilience: A Space Syntax Approach to Analyzing Urban Public Spaces. Sustainability 2025, 17, 5937. https://doi.org/10.3390/su17135937
Li Y, Wang M, Wang B, Liang Y. Bridging Subjective and Objective Dimensions of Resilience: A Space Syntax Approach to Analyzing Urban Public Spaces. Sustainability. 2025; 17(13):5937. https://doi.org/10.3390/su17135937
Chicago/Turabian StyleLi, Yunyan, Miao Wang, Binyan Wang, and Yuchen Liang. 2025. "Bridging Subjective and Objective Dimensions of Resilience: A Space Syntax Approach to Analyzing Urban Public Spaces" Sustainability 17, no. 13: 5937. https://doi.org/10.3390/su17135937
APA StyleLi, Y., Wang, M., Wang, B., & Liang, Y. (2025). Bridging Subjective and Objective Dimensions of Resilience: A Space Syntax Approach to Analyzing Urban Public Spaces. Sustainability, 17(13), 5937. https://doi.org/10.3390/su17135937