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Seasonally disparate responses of surface thermal environment to 2D/3D urban morphology

机译：Seasonally disparate responses of surface thermal environment to 2D/3D urban morphology

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摘要

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.

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