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Urban thermography is a non‐invasive measurement technique commonly used for building diagnosis and energy efficiency evaluation. The physical interpretation of thermal images is a challenging task because they do not necessarily depict the real temperature of the surfaces, but one estimated from the measured incoming radiation. In this sense, the computational rendering of a thermal image can be useful to understand the results captured in a measurement campaign. The computer graphics community has proposed techniques for light rendering that are used for its thermal counterpart. In this work, a physically based simulation methodology based on a combination of the finite element method (FEM) and ray tracing is presented. The proposed methods were tested using a highly detailed urban geometry. Directional emissivity models, glossy reflectivity functions and importance sampling were used to render thermal images. The simulation results were compared with a set of measured thermograms, showing good agreement between them.

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The objective of this work is to represent in a compact and synthetic way surface temperatures at different points of interest throughout an urban scene, by building 4π Thermograms. From a geometrical approach, combining thermography and photographic techniques, a panoramic thermogram is assembled, which enables all directions to be seen from one position. This spherical representation of the data permits to observe the radiative phenomena in a spatialized way allowing its quantification and better understanding. Spatialized distribution of radiation could be expressed as an average temperature weighted by the area of all objects surrounding the measuring point. This emerges as an interesting alternative for measuring the mean radiant temperature in a complex urban scene where multiple heterogeneous surfaces must be considered.