使用极端气温和首尔实时人口数据进行昼间城市热风险评估
Cheolhee Yoo1,2, Jungho Im3, Qihao Weng1,2
1JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
iScience
|October 25, 2023
概括
这项研究引入了一种使用实时人口和温度数据的新日间热风险评估框架. 它准确地绘制了城市热风险,显示了明确的昼夜模式,以指导热适应策略.
科学领域:
- 环境科学 环境科学
- 城市规划 城市规划
- 公共卫生 公共卫生
背景情况:
- 之前的热风险评估在热源识别和动态人口分布方面缺乏准确性.
- 城市热风险日益令人担忧,需要改进评估方法.
研究的目的:
- 开发和验证日间热风险评估框架,使用时空空气温和实时人口数据.
- 为韩国首尔生成动态白天和夜间热风险地图.
主要方法:
- 使用堆叠机器学习模型来导出极端空气温度用于危险评估.
- 使用实际人口密度和使用人口和社会经济指标的脆弱性来计算暴露.
- 通过整合危险,暴露和脆弱性组件生成日间热风险地图.
主要成果:
- 观察到明显的日间空间热风险模式,高风险区域在白天集中在城市核心,并在晚上分散.
- 白天热风险与与热有关的疾病比率有很强的相关性 (R=0.8).
- 该框架准确地捕捉了与热有关的疾病发病率的时间波动.
结论:
- 拟议的日间热风险评估框架有效地纳入了空间时间温度和实时人口数据等动态因素.
- 这些发现为制定针对性,特定地点的城市热情事件的适应和应对计划提供了宝贵的见解.
- 这种方法提高了对城市热力学动态的理解,并支持公共卫生干预措施.
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