Anisotropy of urban surface temperatures: A numerical modelling approach

The three-dimensional structure that characterizes urban areas presents challenges to remote sensing studies. Anisotropic surface radiative emissions can cause remotely-sensed measurements to suffer from biased representations of climatically important variables such as surface temperature. The location and orientation of a remote sensor, and the nature of the surface, directly affects the output obtained and therefore, must be taken into account. A numerical model that attempts to portray the three-dimensional structure of the urban surface is presented and its role in influencing sensor view factors is demonstrated. The complexities of the geometric and radiative validation of the model are discussed. The results show very good agreement exists between modelled and measured temperatures. The model is then used to gain insights into strategies for correctly interpreting remotely-sensed radiative measurements from urban surfaces. The role of anisotropy is examined over a range of sensor-surface orientations and an approach for estimating the complete surface temperature is presented.