通过智能城市数字双胞胎评估和预测集体城市热量暴露
Xiyu Pan1, Dimitris Mavrokapnidis2, Hoang T Ly1
1School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Dr NW, Atlanta, GA, 30332, USA.
Scientific reports
|April 26, 2024
概括
智能城市数字双胞胎 (SCDT) 为评估和预测城市热量暴露提供了一种新的方法. 这项技术集成实时数据来预测热风险,增强公共安全,并启用积极的缓解策略.
科学领域:
- 环境科学与工程环境科学与工程
- 城市规划和智能城市
- 公共卫生和公共安全.
背景情况:
- 城市人口的增加,气候变化和城市热岛效应加剧了城市的热暴露风险.
- 现有的热暴露评估缺乏精细的时空细节和人类移动和气象数据的整合.
- 积极的减轻热暴露需要先进的评估工具,提供综合,实时和预测性见解.
研究的目的:
- 开发和评估智能城市数字双胞胎 (SCDT) 以进行全面的城市热暴露评估和预测.
- 通过整合气象数据和人类集体暴露,弥补细度空间时间热暴露信息的差距.
- 通过预测建模和决策支持能力,实现主动的热暴露缓解措施.
主要方法:
- 在乔治亚州哥伦布实施气象传感器和计算机视觉技术,以收集温度,湿度和行人交通数据.
- 将收集的数据整合到一个集体温度湿度指数 (THI) 中,以实现整体的热暴露度量.
- 利用时间序列预测模型和人群模拟来基于SCDT数据进行短期热暴露预测.
主要成果:
- 开发的SCDT成功获取和整合了各种城市环境和人类流动性数据.
- 该系统展示了计算集体THI的能力,反映了热量和湿度对人口的影响.
- 产生了短期热暴露预测,展示了主动公共安全干预的潜力.
结论:
- 智能城市数字双胞胎 (SCDT) 显示出提高城市热暴露评估和预测的巨大潜力.
- SCDT为城市官员提供了一种有价值的工具,以发现,预测和减轻社区对极端高温事件的暴露.
- 这种方法可以改善城市的性和公共安全,面对全球气温上升和城市化.
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