Abstract
Abstract. Thermography is a robust method for detecting thermal irregularities on the roof of the buildings as one of the main energy dissipation parts. Recently, UAVs are presented to be useful in gathering 3D thermal data of the building roofs. In this topic, the low spatial resolution of thermal imagery is a challenge which leads to a sparse resolution in point clouds. This paper suggests the fusion of visible and thermal point clouds to generate a high-resolution thermal point cloud of the building roofs. For the purpose, camera calibration is performed to obtain internal orientation parameters, and then thermal point clouds and visible point clouds are generated. In the next step, both two point clouds are geo-referenced by control points. To extract building roofs from the visible point cloud, CSF ground filtering is applied, and the vegetation layer is removed by RGBVI index. Afterward, a predefined threshold is applied to the normal vectors in the z-direction in order to separate facets of roofs from the walls. Finally, the visible point cloud of the building roofs and registered thermal point cloud are combined and generate a fused dense point cloud. Results show mean re-projection error of 0.31 pixels for thermal camera calibration and mean absolute distance of 0.2 m for point clouds registration. The final product is a fused point cloud, which its density improves up to twice of the initial thermal point cloud density and it has the spatial accuracy of visible point cloud along with thermal information of the building roofs.
Highlights
Considering the growing importance of the optimal use of energy and the allocation of one-third of total energy consumption to the building sector, there is a need to model the current status of energy performance in the buildings (González et al, 2012)
This study has proposed a method for 3D thermal mapping of building roofs and suggested the combination of visible and thermal point cloud to address the problem of low-resolution thermal imagery
To generate a thermal point cloud, internal orientation parameters are needed, which they were obtained through thermal camera calibration
Summary
Considering the growing importance of the optimal use of energy and the allocation of one-third of total energy consumption to the building sector, there is a need to model the current status of energy performance in the buildings (González et al, 2012). The thermal inspection of the building roof is of particular importance because it is one of the main sources of energy loss. Detecting and fixing defects will increase the life of the roof and, will save energy and costs. To visualize energy performance and simultaneously measure and interpret it, there is a need for 3D thermal modeling (Borrman et al, 2013). Iwaszczuk and Stilla (2017) textured 3D building model in CityGML format with thermal images. For this purpose, a line-based model-to-image matching was used
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
