Dynamic Risk Assessment of Wildland-Urban Interface Fires

TL;DR

This paper introduces a novel dynamic risk assessment method for WUI fires that effectively captures evolving risks over time, improving decision-making for fire prevention and control.

Contribution

It presents an innovative framework combining dynamic evaluation, grey incidence analysis, and optimization to assess and rank fire risks dynamically, surpassing static assessment limitations.

Findings

Effectively captures dynamic fire risk evolution patterns.

Simplifies computational process for risk assessment.

Provides a scientific basis for proactive fire management.

Abstract

Wildland-Urban Interface (WUI) fires represent a compound disaster resulting from the interactions between natural ecosystems and human settlements, characterized by significantly dynamic evolving risks. However, most current risk assessment studies are based on static frameworks, which struggle to effectively capture the dynamic changes in risk over time. To address this issue, this paper proposes an innovative method that integrates a dynamic evaluation matrix, grey incidence analysis, and an optimization model for the dynamic risk assessment of WUI fires. This method incorporates time-series data by constructing a dynamic evaluation matrix, subsequently calculates the weighted standardized matrix for each evaluated area and its local volume matrices relative to the positive and negative ideal matrices. The dynamic differences between the evaluated areas and the ideal state are quantified by calculating the grey incidence degree, and an optimization model is established to solve for the superiority degree used for risk ranking. Research demonstrates that this method not only simplifies the computational process but also effectively captures the dynamic evolution patterns of fire risk across different areas, enabling refined risk classification. Compared to existing static methods, this framework overcomes their limitation in adequately representing risk dynamics, providing a more scientific basis for decision-making in the dynamic management and proactive prevention and control of WUI fires.