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Article

Predicting the Integrated Fire Resistance of Wildland–Urban Interface Plant Communities by Spatial Structure Analysis Learning for Shanghai, China

by
Manqing Yao
,
Deshun Zhang
*,
Ruilin Zhu
,
Zhen Zhang
and
Mohamed Elsadek
College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
*
Author to whom correspondence should be addressed.
Forests 2024, 15(7), 1266; https://doi.org/10.3390/f15071266 (registering DOI)
Submission received: 13 June 2024 / Revised: 9 July 2024 / Accepted: 10 July 2024 / Published: 20 July 2024
(This article belongs to the Section Urban Forestry)

Abstract

Abstract: Fire is a prevalent hazard that poses a significant risk to public safety and societal progress. The continuous expansion of densely populated urban areas, exacerbated by global warming and the increasing intensification of urban heat islands, has led to a notable increase in the frequency and severity of fires worldwide. Incorporating measures to withstand different types of calamities has always been a crucial aspect of urban infrastructure. Well-designed plant communities play a pivotal role as a component of green space systems in addressing climate-related challenges, effectively mitigating the occurrence and spread of fires. This study conducted field research on 21 sites in the green belt around Shanghai, China, quantifying tree morphological indexes and coordinate positions. The spatial structure attributes of different plant communities were analyzed by principal component analysis, CRITIC weighting approach, and stepwise regression analysis to build a comprehensive fire resistance prediction model. Through this research, the relationship between community spatial structures and fire resistance was explored. A systematic construction of a prediction model based on community spatial structures for fire resistance was undertaken, and the fire resistance performance could be quickly judged by easily measured tree morphological indexes, providing valuable insights for the dynamic prediction of fire resistance. According to the evaluation and ranking conducted by the prediction model, the Celtis sinensis, Sapindus saponaria, Osmanthus fragrans, Koelreuteria paniculata, and Distylium racemosum + Populus euramericana ‘I-214’ communities exhibited a high level of fire resistance. On the other hand, the Koelreuteria bipinnata + Ligustrum lucidum, Ginkgo biloba + Camphora officinarum + Ligustrum lucidum, and Ligustrum lucidum + Sapindus saponaria communities obtained lower scores and were positioned lower in the ranking. It is emphasized that the integration of monitoring and regulation is essential to ensure the ecological integrity and well-being of green areas in the Wildland–Urban Interface.
Keywords: urban greening; plant community; fire resistance; spatial structure; prediction model; surface litter urban greening; plant community; fire resistance; spatial structure; prediction model; surface litter

Share and Cite

MDPI and ACS Style

Yao, M.; Zhang, D.; Zhu, R.; Zhang, Z.; Elsadek, M. Predicting the Integrated Fire Resistance of Wildland–Urban Interface Plant Communities by Spatial Structure Analysis Learning for Shanghai, China. Forests 2024, 15, 1266. https://doi.org/10.3390/f15071266

AMA Style

Yao M, Zhang D, Zhu R, Zhang Z, Elsadek M. Predicting the Integrated Fire Resistance of Wildland–Urban Interface Plant Communities by Spatial Structure Analysis Learning for Shanghai, China. Forests. 2024; 15(7):1266. https://doi.org/10.3390/f15071266

Chicago/Turabian Style

Yao, Manqing, Deshun Zhang, Ruilin Zhu, Zhen Zhang, and Mohamed Elsadek. 2024. "Predicting the Integrated Fire Resistance of Wildland–Urban Interface Plant Communities by Spatial Structure Analysis Learning for Shanghai, China" Forests 15, no. 7: 1266. https://doi.org/10.3390/f15071266

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