Author
Listed:
- Yuning Feng
(School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China)
- Chuyun Cheng
(Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
Beijing Key Laboratory of Spatio-Temporal Perception and Urban Resilience, Beijing 100871, China)
- Zhengxiong Lei
(School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)
- Zehao Shen
(School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)
- Lun Wu
(Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
Beijing Key Laboratory of Spatio-Temporal Perception and Urban Resilience, Beijing 100871, China)
- Cong Liao
(CAUPD Beijing Planning & Design Consultants Ltd., Beijing 100044, China)
- Yuan Tian
(Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
Beijing Key Laboratory of Spatio-Temporal Perception and Urban Resilience, Beijing 100871, China)
Abstract
Urban fire prevention is shifting from reactive response to proactive risk governance, yet current approaches often overlook risk-type heterogeneity, spatial dependencies, and underlying behavioral mechanisms, especially equitable risk distribution among vulnerable groups. To address this, this study integrates the Pressure–State–Response (PSR) model with environmental criminology theories (Routine Activity Theory (RAT) and Crime Pattern Theory (CPT)) to couple macro social causal chains with micro behavioral–spatial mechanisms. Using data from the digital urban management system of Shenzhen’s Guangming District in 2019, four fire risk event types are examined: electric bike charging violations (EB), unauthorized power wiring (PW), water heater misuse (WH), and aging gas pipelines (GP). Spatial error models explain 82–89% of the variance across fire risk event types, and spatial 5-fold cross-validation shows minimal performance decline (ΔR 2 = 0.03–0.08), confirming robust prediction without overfitting. Key findings include: (1) elderly proportion is significantly positively associated with WH and PW (coefficients = 2.64 and 3.06, p < 0.01); (2) restaurant density has a consistently positive association with all four risk types (coefficients = 0.24–0.60, p < 0.01); (3) functional diversity and connectivity exhibit dual patterns, showing negative associations with more visible, easily detectable violations (PW, GP) but positive relationships with relatively concealed behaviors (EB); (4) reported safety deficiencies display strong positive associations with all fire risk event types and can therefore serve as an effective early-warning indicator for broader fire risk. These results support risk-specific, equity-oriented prevention strategies that prioritize vulnerable groups and high-risk environments. The validated PSR–RAT/CPT framework provides a novel theoretical basis for targeted fire risk governance and advances safe, resilient, inclusive cities aligned with Sustainable Development Goal 11.
Suggested Citation
Yuning Feng & Chuyun Cheng & Zhengxiong Lei & Zehao Shen & Lun Wu & Cong Liao & Yuan Tian, 2026.
"From Rescue to Prevention: A Comprehensive Analysis Framework for Urban Fire Risks Based on the PSR Model and Environmental Criminology Theory,"
Sustainability, MDPI, vol. 18(12), pages 1-20, June.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:12:p:5795-:d:1961274
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