Increasing urban tree canopy (UTC) has been widely recognized as an effective means for urban heat mitigation and adaptation. While numerous studies have shown that both percent cover of UTC and its spatial configuration can significantly affect urban temperature, the pathways governing these relationships are largely unexplored. Here we present a cross-city comparison aiming to fill this gap by explicitly quantifying the pathways on which percent cover of UTC and its spatial configuration affect land surface temperature (LST) using structural equation modeling (SEM), based on UTC mapped from high resolution imagery and LST derived from Landsat thermal bands. We found: 1) Although both the direct and indirect pathways significantly affected LST regardless of scales and cities, the direct pathway played a more important role in affecting LST in Baltimore, Beijing, and Shenzhen. In contrast, an opposite result was found in Sacramento, likely due to the effects of buildings and their interactions with UTC. 2) Similarly, the direct pathway of mean patch size (MPS) and mean shape index (MSI) played a more important role in affecting LST than their indirect effects via altering edge density (ED). Our results highlighted the necessity for discomposing the effects of different spatial configuration variables on LST. Understanding the pathways through which UTC affects LST can provide insights into urban heat mitigation and adaptation.
Keywords: Path analysis; Structural equation model; Urban heat mitigation.
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