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The driving mechanisms of urban surface thermal environments usually differ with season. However, to date, the seasonal differences in the impacts of two-dimensional (2D) and three-dimensional (3D) building and tree morphologies on land surface temperature (LST) remain poorly understood. Additionally, there has yet to be a quantitative attempt to separate the direct effects of building and tree morphologies on LST from the indirect effects from 3D perspectives. Here, using Nanjing, China as an example, we investigated the seasonally disparate responses of LST to the 2D and 3D building and tree morphologies, by combining boosted regression trees and a structural equation model (SEM). Our findings show that the predominant factor that affects the spatial pattern of LST is the percent cover of buildings (PER_Build) in spring and summer, while the sky view factor (SVF) dominates LST variations in autumn and winter. The LST responsiveness to changes in these factors also showed a large seasonal variation. In summer, LST increased with PER_Build, and the greatest warming effect occurred when the building surface and tree canopy fractions were lower than 25% and 40%, respectively. In winter, by comparison, the variations in SVF and PER_Tree led to a larger change in LST. Further results using the SEM model suggest that LST variation is governed by more 2D building structures in spring and summer, whereas 3D building structures have a more dominant impact on LST in autumn and winter. Most of the overall impacts resulting from the 3D building and horizontal tree structures are direct throughout each season. However, the overall impacts of the 2D building structure on LST are mainly direct in spring and summer yet indirect in autumn and winter. In all seasons, the indirect impacts of 2D and 3D building structures on LST primarily originate from the horizontal and vertical tree structures, respectively. We consider that these findings can guide designing optimization strategies for urban heat mitigation for different seasons from 2D and 3D perspectives. [Display omitted] • Responses of LST to 2D/3D urban morphology indicators are analyzed across seasons. • Direct and indirect impacts of building/tree on LST are studied from 3D perspective. • Responses of LST to changes in 2D/3D morphology indicators are seasonally dependent. [ABSTRACT FROM AUTHOR]

Separate impacts of building and tree on the urban thermal environment have been studied extensively, but their combined impacts, especially from both the horizontal (i.e., two-dimensional (2D)) and vertical (i.e., three-dimensional (3D)) perspectives remain largely unclear. Based on satellite thermal data and elaborate 2D and 3D urban morphology, herein we simultaneously investigate the separate and combined impacts of building and tree over Nanjing in China from both the 2D and 3D perspectives. We further examine the day–night contrast together with the sensitivity of such impacts to scale. Our results show that, when compared with urban structures from a single dimension, the combination of 2D and 3D structures is more capable of predicting urban land surface temperatures (LSTs) for both day and night. The assessments further illustrate that the separate and combined impacts of building and tree on LSTs are usually more significant when the spatial scale increases. As for the separate impacts of building and tree, 2D structure affects more urban thermal environment than 3D structure at all spatial scales during the day, but an opposite trend occurs at night. Moreover, for the combined impact of building and tree on LST across different scales, daytime and nighttime LSTs are respectively dominated by 2D and 3D building structures. Combining 2D and 3D structures improves the explained LST variation by 7.3%–11.1% and 25.3%–37.7% for day and night, respectively when compared to using 2D structures only. These findings emphasize the need to incorporate both 2D and 3D urban morphology to improve the urban thermal environment. [Display omitted] • Separate and combined impacts of building and tree on LST are analyzed from both 2D and 3D perspectives. • Sensitivity of the relative importance of 2D and 3D structures on LST to scale is examined. • Combining 2D and 3D structures better predicts LST than features of a single dimension. • 2D building structure affects more LST than 3D building structure during the day, but opposite at night. [ABSTRACT FROM AUTHOR]

The Universal Thermal Climate Index (UTCI) is an important and frequently used indicator for evaluating thermal comfort. However, there is a lack of city-scale UTCI mapping over urban agglomerations during heat waves, and of studies of the variation of UTCI-based urban heat island intensities across cities. In addition, there is a need to evaluate the relationships among UHI intensities calculated by different types of temperature. In this study of the Yangtze River Delta urban agglomeration (YRDUA), we conducted city-scale UTCI mapping during periods of heat waves, based largely on satellite data. We then compared the UHI intensities in three megacities (Nanjing, Shanghai, and Hangzhou) in terms of the UTCI, and distinguished the differences between UHI intensities based on different types of temperature. Our principal findings are as follows: (1) The UTCI varies considerably with land cover type, with values generally higher in urban areas. Although the spatial pattern of UTCI and air temperature appears similar, over urban surfaces the former indicator is significantly higher than the latter. (2) The areas affected by (very) strong thermal stress (quantified by the UTCI) expanded by 18% and 36.2%, respectively, during daytime and nighttime over the YRUDA from 2002 to 2018. The increase occurred mainly in city peripheries where rapid urbanization has occurred. (3) The UTCI-based UHI intensity (UHII) is lower than those based on land surface temperature (LST) and mean radiant temperature, but greater than those based on surface air and dew-point temperature. The difference among these UHIIs (i.e., UTCI- and other temperature-based measures) over the three selected megacities are relatively small in the day, but they are relatively large at night. Our results are potentially valuable for facilitating city-scale UTCI mapping and for evaluating thermal comfort at the regional scale. Image 1 • City-scale UTCI mapping is achieved mainly using satellite data. • Spatiotemporal patterns of UTCI over an urban agglomeration are evaluated. • Relationships of UTCI with other surface properties are examined. • UTCI-based UHI intensity is compared with those obtained by other temperatures. [ABSTRACT FROM AUTHOR]