The Role of Urban Vegetation in Mitigating Fire Risk Under Climate Change: A Review

The confluence of global warming, the urban heat island effect, and alterations in the nature of underlying surfaces has led to a continuous escalation in the frequency, scale, and intensity of fires within urban green spaces. Mitigating or eliminating the adverse effects of such fires on the service functions of urban ecosystems, while enhancing the resilience of urban greening systems in disaster prevention and risk reduction, has become a pivotal challenge in modern urban development and management. Academic focus has progressively broadened from isolated urban and forest domains to encompass the more intricate environments of the Wildland–Urban Interface (WUI) and urban–suburban forests, with a particular emphasis on the distinctive characteristics of urban greening and in-depth research. This study employs a combination of CiteSpace bibliometric analysis and a narrative literature review to comprehensively examine three critical aspects of urban fire safety as follows: (1) the evaluation of the fire-resistant performance of landscape plants in urban green spaces; (2) the mechanisms of fire behavior in urban greening systems; and (3) the assessment and prediction of urban fire risks. Our findings indicate that landscape plants play a crucial role in controlling the spread of fires in urban green spaces by providing physical barriers and inhibiting combustion processes, thereby mitigating fire propagation. However, the diversity and non-native characteristics of urban greenery species present challenges. The existing research lacks standardized experimental indicators and often focuses on single-dimensional analyses, leading to conclusions that are limited, inconsistent, or even contradictory. Furthermore, most current fire spread models are designed primarily for forests and wildland–urban interface (WUI) regions. Empirical and semi-empirical models dominate this field, yet future advancements will likely involve coupled models that integrate climate and environmental factors. Fire risk assessment and prediction represent a global research hotspot, with machine learning- and deep learning-based approaches increasingly gaining prominence. These advanced methods have demonstrated superior accuracy compared to traditional techniques in predicting urban fire risks. This synthesis aims to elucidate the current state, trends, and deficiencies within the existing research. Future research should explore methods for screening highly resistant landscape plants, with the goal of bolstering the ecological resilience of urban greening systems and providing theoretical underpinnings for the realization of sustainable urban environmental security.