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• W3105642833 startingPage "103979" @default.
• W3105642833 abstract "Using land surface temperatures (LST) derived from remotely sensed data, numerous studies have shown that not only urban areas are warmer than surrounding rural areas, but within urban areas, there are large spatial variations in temperature. Few studies, however, have investigated the spatial variation of air temperature within a city. Using air temperature data collected from 117 weather stations in Shenzhen for the year of 2017, we quantified the within-city spatial pattern of air temperature and its nocturnal and seasonal variability. We further investigated the quantitative relationship between air temperature and LST and compared their spatiotemporal patterns. We found that: 1) Air temperature varied greatly in space, showing very strong spatial heterogeneity and having large nocturnal and seasonal variability; 2) The spatial and temporal variation is more prominent during extreme heat days, during which the difference of hourly maximum temperature among stations could reach 8.7 °C around 16:00 and remain as high as 8.6 °C until 23:00, indicating that locations in cities with higher temperatures may suffer more intensive and longer excessive urban heat, and thereby global warming may exacerbate the difference in air temperature at the local scale; 3) LST had significantly positive correlations with air temperature, especially in the summer night, but their cool and hot spots did not always overlap in space. Results can enhance understanding of the spatial heterogeneity of the urban thermal environment and have practical implications on excessive urban heat mitigation and adaptation in an increasingly warming global climate." @default.
• W3105642833 created "2020-11-23" @default.
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• W3105642833 date "2021-02-01" @default.
• W3105642833 modified "2023-10-14" @default.
• W3105642833 title "Within-city spatial and temporal heterogeneity of air temperature and its relationship with land surface temperature" @default.
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• W3105642833 doi "https://doi.org/10.1016/j.landurbplan.2020.103979" @default.
• W3105642833 hasPublicationYear "2021" @default.
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