Publications

Wang, DD; Chen, YH; Hu, LQ; Voogt, JA; He, XY (2022). Satellite-based daytime urban thermal anisotropy: A comparison of 25 global cities. REMOTE SENSING OF ENVIRONMENT, 283, 113312.

Abstract
Remotely sensed land surface temperature (LST) has become one of primary observational sources for urban climate research. However, LST is subject to considerable angular variation, particularly in urban areas caused by a large variation of sensor viewing angles and non-isothermal facades of 3D urban structures. Anisotropy varies seasonally and diurnally, and is sensitive to sensor viewing geometry, solar angles, and urban surface properties. Current studies focus on urban thermal anisotropy of individual cities, comparative study and the resultant driving factor analysis are still lacking. To bridge this critical knowledge gap, a systematic comparative assessment of satellite-based urban thermal anisotropy is required. Here, we modify and validate a satellite-based anisotropy estimation approach and compare the seasonal and diurnal anisotropy variations over 25 global cities to answer the following research questions: 1) How do the anisotropy magnitude and profile shapes vary among different cities? 2) What are the factors influencing the anisotropy? The results show that off-nadir observations are up to 3.5 K cooler on average than nadir LST during summer whereas the effective anisotropy ranges between 2.1 K and 5.8 K for all cities. Winter anisotropy is much smaller (similar to 1 K), where the warm or cold bias is determined by solar zenith angle (morning/afternoon overpasses), and its bias magnitude is linearly proportional to the sensor zenith angle. Urban thermal anisotropy is partly influenced by geographic location (e.g., latitude, longitude), urban vegetation (measured by NDVI) and urban geometry (building height-street width ratio, h/w), where low latitude cities or cities with less vegetation tend to have a greater angular variation in summer, and the anisotropy tends to increase with more complex urban morphology (i.e., higher building aspect ratio). High vegetation cover makes the anisotropy distribution shape more asymmetric along the cross-track direction (or sensor zenith angle). Our findings help understand the seasonal and diurnal impact of anisotropy for wide-swath LST applications in cities and offers insights for addressing anisotropy in future satellite products.

DOI:
10.1016/j.rse.2022.113312

ISSN:
1879-0704