评估得克萨斯州奥斯汀市的城市火灾脆弱性以及消防站和医院的可及性

Akhil Mandalapu, Kijin Seong, Junfeng Jiao
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引用次数: 0

摘要

人为气候变化增加了火灾的频率和强度。尽管火灾造成了广泛的后果,但目前的研究在很大程度上忽视了城市火灾及其相关的脆弱性。本研究旨在确定火灾脆弱性的模式,绘制出火灾脆弱性高且消防站和医院交通不便的地区,并最终确定导致火灾事故增加的因素。研究采用主成分分析法制定了火灾脆弱性指数,该指数由反映健康状况和社会环境因素的变量组成。为确定医院和消防站等资源的相对可达性,进行了增强型两步浮动集水区(E2SFCA)分析。利用普通最小二乘法(OLS)回归和地理加权回归(GWR)来确定与较高火灾事故次数相关的因素。火灾脆弱性分析结果表明,奥斯汀东部外围地区和中北部地区是火灾高发区。此外,东部外围地区的消防站和医院的可达性也有所下降。最后,GWR 分析结果表明,健康脆弱性与火灾事故之间存在不同程度的负相关关系,而与社会环境脆弱性之间存在正相关关系。与 OLS(R2:0.056)相比,GWR 模型(R2:0.332)能够预测更大范围的差异。这项研究的结果表明,社会环境脆弱的地区可能会面临更多的火灾事故,而且医院和消防站的使用率也会降低。这些发现可以为公共卫生官员、城市规划者和应急服务部门提供信息,帮助他们制定有针对性的策略,减轻火灾事故造成的伤害。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating urban fire vulnerability and accessibility to fire stations and hospitals in Austin, Texas
Anthropogenic climate change has increased the frequency and intensity of fires. Despite their widespread consequences, current research has largely overlooked urban fires and their associated vulnerability. This study seeks to identify patterns of fire vulnerability, map out areas with high fire vulnerability and limited access to fire stations and hospitals, and ultimately determine the factors contributing to increased fire incidents. Principal Component Analysis was used to develop a fire vulnerability index comprising variables capturing health status and socio-environmental factors. Enhanced 2-step floating catchment area (E2SFCA) analysis was conducted to determine relative accessibility to resources such as hospitals and fire stations. Ordinary least squares (OLS) regression and geographically weighted regression (GWR) were utilized to determine factors associated with higher fire incident counts. The results of the fire vulnerability analysis highlight areas of high fire vulnerability in the eastern periphery and the north-central parts of Austin. Moreover, the eastern periphery experiences decreased accessibility to fire stations and hospitals. Finally, the results of the GWR analysis highlight a varied negative relationship between health vulnerability and fire incidents and a positive relationship with socio-environmental vulnerability. The GWR model (R2: 0.332) was able to predict a greater extent of the variance compared to OLS (R2: 0.056). Results of this study underscore that areas with socio-environmental vulnerabilities are likely to face a higher number of fire incidents and have reduced access to hospitals and fire stations. These findings can inform public health officials, city planners, and emergency services departments in developing targeted strategies to mitigate the harm caused by fire incidents.
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