基于ECOSTRESS地表温度和手机信令数据的城市人口热环境暴露风险评价——以西安市为例

全球气候变暖和城市热岛效应的双重影响使人类社会面临的极端高温风险日益加剧，给城市人口健康和社会经济可持续发展带来严峻挑战，科学评估城市热环境下人口暴露风险已成为当前学术界关注的热点领域。论文基于ECOSTRESS地表温度数据和手机信令数据，以西安市为例，在城市地表温度和人口时空变化分析基础上，构建城市人口暴露风险评价模型，揭示精细化时空尺度上的人口暴露风险时空格局及其动态演变特征。结果表明：① 西安市夏季一天内的地表温度呈现出明显的波动特征，昼夜地表温度差异较大，白天平均温度为35.5 ℃，夜间平均温度为21.5 ℃，白天地表温度空间分布相比夜间具有更明显的空间异质性，且日内所有时刻均存在不同强度的城市热岛效应，热岛分布的变化表现出从聚集状态向离散状态再过渡至聚集状态的特征。② 西安市人口分布呈单中心结构，73.6%的人口都分布在三环以内，且沿中轴线集中的现象显著，昼夜人口形成了“白天向心、夜间离心”的分布特征。③ 人口暴露的中、高与极高风险区主要呈散点式分布在城市中心区域，且86.6%的极高风险区位于三环以内，而无风险和低风险区主要集中连片分布在城市外围。④ 导致昼夜人口暴露风险差异的不同主导类型面积占比依次为温度主导型(37.9%)>共同主导型(31.5%)>人口主导型(30.6%)。研究可为城市人口暴露风险区域的识别及制定针对性的适应性策略提供参考。

Population exposure risk to urban extreme heat environment based on ECOSTRESS land surface temperature and mobile phone signaling data: A case study of Xi’an City

The dual effects of global warming and urban heat island have increasingly exacerbated the extreme heat risk, and given severe challenges to the health of urban residents and socioeconomic development. Accurately assessing the population exposure to urban extreme heat environment has become a current research hotspot. In this study, we used the new ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and mobile phone signaling data to explore the spatiotemporal variation of land surface temperature and population in Xi'an City, developed a population exposure risk assessment model, and revealed the spatiotemporal pattern and dynamic characteristics of the exposure risk on a refined scale. The results show that: 1) The diurnal cycling of land surface temperature in summer showed obvious fluctuation characteristics, especially a large difference between day and night. The average temperature in the daytime was 35.5 ℃ and 21.5 ℃ at night, and land surface temperature exhibited more spatial variations in the daytime. The urban heat island effect of different intensities existed at all times of the day, and it varied from aggregation state to discrete state and then to aggregation state. 2) Nearly three quarters (73.6%) of the population were distributed within the third ring road with a single center structure, and the population was concentrated along the central axis. The population distribution change displayed the characteristics of "centripetal in the daytime and centrifugal at night". 3) The medium risk, high risk, and extremely high risk areas of population exposure were mainly scattered in the central area of the city, and 86.6% of the extremely high risk areas were located within the third ring road, while the negligible risk and low risk areas were mainly concentrated in the periphery. 4) The dominant factors leading to difference of heat exposure risk were grouped into three types including temperature-dominated, population-dominated, and co-dominated, and their proportion to the total urban area were 37.9%, 30.6%, and 31.5%, respectively. This research can provide a scientific reference for the heat exposure risk identification and targeted adaptive strategies.