An advanced geometric model to simulate thermal anisotropy time-series for simplified urban neighborhoods (GUTA-T)
An advanced geometric model to simulate thermal anisotropy time-series for simplified urban neighborhoods (GUTA-T)
复制标题
用于模拟简化城市社区热各向异性时间序列的高级几何模型 (GUTA-T)
DOI：
10.1016/j.rse.2019.111547
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发表时间：
2020-02
影响因子：
13.5
通讯作者：
Jinfei Wang
中科院分区：
文献类型：
--
作者：
D;an Wang;Yunhao Chen;Leibin Wang;E. Scott Krayenhoff;James A. Voogt;Jinfei Wang
城市建筑物表面定向辐射表面温度测量的各向异性预计具有很强的时间变化。然而，一个模型的能力，以模拟城市热各向异性（UTA）的时间变化和反演能力尚未开发。本文研究了UTA随时间的变化与地表组分温度差异的关系。本文在已有的模拟不同密度城市街区热各向异性的几何模型的基础上，提出了一个先进的几何模型系统GUTA-T，它通过晴空下温度对比度对太阳天顶角θ的依赖性来反映UTA的时间变化。一个3-D微尺度城市表面温度模型和传感器视图模型相结合，以生成一个合成的UTA数据集的各种简化的城市几何形状，并与评估GUTA-T。结果表明，参数反演是敏感的太阳表面传感器的几何形状。用GUTA-T模拟了各向异性的季节性和逐时性行为，对于（40°，90°）、（60°，270°）、（60°，180°）和（40°，130°）的视角天顶角和方位角（θv，φv），平均绝对差分别为1.06 °C、1.25 °C、1.69 °C和1.04 °C。在城市尺度模式上使用日测量值的评估表明，当θs≤ 60°时，模拟的各向异性与由观测的方向温度和高精度计算机模式产生的参考各向异性之间的均方根差为2.02 °C。如果拟用卫星数据校准所提出的模型，则从地面目标区域的另一侧进行第二次定向观测可显著提高模型的性能。使用仅包括少量（例如，θs≤ 30°）或大θs（例如，θs≥ 50°）会降低各向异性时间序列的模拟精度。由于其反演能力，GUTA-T模型有可能模拟和纠正各向异性的时间序列热红外遥感数据，从而提高分析无论是在图像的空间变化，或角城市表面温度的时间变化。
The anisotropy of directional radiative surface temperature measurements over urban building surfaces is expected to have strong temporal variation. However, a model with the capability to simulate the temporal variation of urban thermal anisotropy (UTA) and with inversion abilities has not yet been developed. In this paper, the relationship between the temporal variation of UTA and temperature contrasts among surface components is investigated. Based on a system of previously developed geometric models for simulation of thermal anisotropy in simplified urban neighborhoods of different densities, a system of advanced geometric models, GUTA-T, is proposed that incorporates the temporal variability of UTA through the dependence of temperature contrasts on solar zenith angleθsunder clear skies. A 3-D microscale urban surface temperature model and a sensor view model are combined to generate a synthetic UTA dataset for a variety of simplified urban geometries and with which to evaluate GUTA-T. The results show that parameter inversions are sensitive to sun-surface-sensor geometries. The seasonal and hourly behavior of anisotropy is simulated by GUTA-T with mean absolute differences of 1.06 °C, 1.25 °C, 1.69 °C and 1.04 °C for the view zenith and azimuth angles (θv,φv) of (40°, 90°), (60°, 270°), (60°, 180°) and (40°, 130°), respectively. Evaluation using diurnal measurements over an urban scale model shows that the root mean square difference between simulated anisotropy and the reference anisotropy generated from observed directional temperatures and a high-accuracy computer model is 2.02 °C forθs≤ 60°. If the proposed model is to be calibrated with satellite data, a second directional observation from the opposite side of the surface target area can improve model performance significantly. Calibrations using samples including only small (e.g.,θs≤ 30°) or largeθs(e.g.,θs≥ 50°) tend to decrease the anisotropy time-series simulation accuracy. Due to its inversion abilities, the GUTA-T model has the potential to simulate and correct anisotropy in time-series thermal infrared remote sensing data, thereby improving the analysis either of spatial variation within an image, or of temporal variation of angular urban surface temperature.
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