Abstract
Abstract. This paper presents a concept for classification of facade elements, based on the material and the geometry of the elements in addition to the thermal radiation of the facade with the usage of a multimodal Unmanned Aerial Vehicle (UAV) system. Once the concept is finalized and functional, the workflow can be used for energy demand estimations for buildings by exploiting existing methods for estimation of heat transfer coefficient and the transmitted heat loss. The multimodal system consists of a thermal, a hyperspectral and an optical sensor, which can be operational with a UAV. While dealing with sensors that operate in different spectra and have different technical specifications, such as the radiometric and the geometric resolution, the challenges that are faced are presented. Addressed are the different approaches of data fusion, such as image registration, generation of 3D models by performing image matching and the means for classification based on either the geometry of the object or the pixel values. As a first step towards realizing the concept, the result from a geometric calibration with a designed multimodal calibration pattern is presented.
Highlights
The European Union initiated in 2012 measurements with the aim to reduce the total energy consumption with 20% by 2020 and with 50% by 2050
This paper introduces a new concept for classification of facade elements exploiting a multimodal based Unmanned Aerial Vehicle (UAV) system, which later can be used for estimating the energy demand for buildings
This approach will be used in this study for generation of 3D models of building facades, since it has proven to result in good 3D models of building facades and by using a multimodal system
Summary
The European Union initiated in 2012 measurements with the aim to reduce the total energy consumption with 20% by 2020 and with 50% by 2050. Different methods for estimating the energy demand for buildings have been performed in several studies, by mainly combining different kinds of data It can be done by combining 3D models with statistical data for larger scale studies, such as for a whole city (Kaden and Kolbe, 2013, Mastrucci et al, 2014). Another common approach is to assess the energy efficiency by acquiring data of building facades using a thermal sensor, by either combining a thermal sensor with a 3D laser scanner (Laguela et al, 2011b) or by generating a 3D model with the acquired thermal images (Gonzalez-Aguilera et al, 2013).
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