Exploring Influencing Factors for Differences in Integral and Complete Urban Surface Temperatures

Complete urban surface temperature (UST) ( $T_{\textrm {c}}$ ) takes into account the total active surface areas and is used to estimate the surface temperature over a 3-D rough surface such as cities. Direct calculations of $T_{\textrm {c}}$ require temperatures of each surface of the urban canopy, which are hard to obtain in actual remote sensing observations. Moreover, solid-angle integral temperature ( $T_{\text {SI}}$ ) calculated using multiangle remote sensing observations has great potential for approaching $T_{\textrm {c}}$ . However, due to varying mechanisms, some differences remain between them. This study uses temperatures of urban facets in 3-D (TUF-3D) and surface-sensor-sun urban model (SUM) models to compute integral temperatures for multiple view angles over various urban forms and investigates the differences between $T_{\textrm {c}}$ and $T_{\text {SI}}$ and the influencing factors. The difference is minimized at VZA $=48^{\circ }$ –70° and VAA $=0^{\circ }$ –360°, and the mean absolute error (MAE) is 0.67 K. Urban canopy geometry (UCG) and solar zenith angles (SZAs) are the important influencing factors. Compared with $T_{\textrm {c}}$ , $T_{\text {SI}}$ underestimates the proportion of the wall. The MAE between $T_{\text {SI}}$ and $T_{\textrm {c}}$ decreases as the wall fraction in the integral domain increases but increases when the wall fraction exceeds a threshold. The upper limit of the optimal integral domain (OID) is basically 70° and the lower limit hovers around 48°, moving away from and then approaching the zenith as the SZA increases. This study evaluates the influencing factors for differences in $T_{\text {SI}}$ and $T_{\textrm {c}}$ . It offers a simple and high-accuracy method for approaching $T_{\textrm {c}}$ which can be used to facilitate research in urban energy balance and urban climate.

I. Introduction

Urban surface temperature (UST) is an important parameter for characterizing the urban thermal environment and estimating surface energy flux. Accurate monitoring of UST and characterization of the urban thermal environment is one of the important contents of sustainable urban development [1], [2], [3]. Thermal infrared remote sensing has become an important means to monitor UST via consistent periodicity, high-spatial resolution, and global coverage. Satellite-retrieved land surface temperature (LST) has been widely applied to investigate urban surface energy balance, heat island effect, and urban climate change [4], [5], [6], [7]. However, the anisotropy of satellite-based LST measurements has been found over structured urban surfaces, which means that the remotely sensed UST varies depending on the direction of the sensor view. This anisotropy results from the angular variation of nonisothermal components and emissivity detected from an instantaneous field of view (IFOV) [8], [9], [10], [11], [12], [13], [14]. Previous studies have demonstrated that LST differences can be up to 10 K between oblique and nadir viewing in winter over Toulouse city center and LST anisotropy can reach 12 K at midday in the summer [11], [15].