Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in Seoul.

ABSTRACT: Previous heat risk assessments have limitations in obtaining accurate heat hazard sources and capturing population distributions, which change over time. This study proposes a diurnal heat risk assessment framework incorporating spatiotemporal air temperature and real-time population data. Daytime and nighttime heat risk maps were generated using hazard, exposure, and vulnerability components in Seoul during the summer of 2018. The hazard was derived from the daily extreme air temperatures obtained using the stacking machine learning model. Exposure was calculated using de facto population density, and vulnerability was assessed using demographic and socioeconomic indicators. The resulting maps revealed distinct diurnal spatial patterns, with high-risk areas in the urban core during

SUBMITTER: Yoo C 

PROVIDER: S-EPMC10590841 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature