Complexity of the relationship between 2D/3D urban morphology and the land surface temperature: a multiscale perspective

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Abstract
Urban morphology is a crucial contributor to urban heat island (UHI) effects. However, few studies have explored the complex effect of 2D/3D urban morphology on UHIs from a multiscale perspective. In this study, we chose the central area of Jinan city, which is commonly known as the “furnace,” as the case study area. The 2D/3D urban morphology indexes-building coverage ratio (BCR) (for assessing the 2D building density), building volume density (BVD) (for assessing the 3D building density), and frontal area index (FAI) (for assessing 3D ventilation conditions) were calculated and derived to investigate the complexity of the relationship between 2D/3D urban morphology and the land surface temperature (LST) at different scales using the maximum information coefficient (MIC) and geographically weighted regression (GWR). The results indicated that (1) these 2D/3D urban morphology indexes are essential factors that are responsible for LST variation, and BCR is the most important urban morphology index affecting LST, followed by BVD and FAI. Importantly, the relationship between the BCR, BVD, FAI, and LST was an inverse U-shaped curve. (2) The relationship between 2D/3D urban morphology and LST variation showed a significant scale effect. With increased grid size, the correlation between the BCR, BVD, and FAI and the LST strengthened, “inflection point” of inverse U-shaped curve significantly declined, and their explanation rate of the LST first increased and then decreased, with a maximum value at the 700 m scale. Additionally, the FAI exerted a stronger negative effect, while the BCR and BVD generally had stronger positive effects on the LST as the grid size increased. This study extends our scientific understanding of the complex effect of urban morphology on the LST and is of great practical significance for multiscale urban thermal environment regulation.
Funding Information
  • The National Social Science Fund of China (No. 18BJY086)

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