## 4 Experimentation on the Case Study
### Photogrammetric and Scanning 3D Reconstruction
The spatial registration of thermographic imagery presents a unique challenge due to inherent data characteristics, including limited spatial resolution, significant geometric variability, and the absence of a direct linear correlation between pixel intensity gradients and radiometric temperature gradients [27]. The aerial thermal scanning revealed mild heat losses, with a limited temperature difference (i.e., less than 6 \({}^{\circ}\)C). This finding indicates a relatively good level of thermal efficiency, suggesting that existing insulation and construction materials are performing adequately in minimising energy leakage. Although the observed temperature differences are minimal, improvements are still possible, as even small enhancements in thermal insulation can lead to significant energy savings and increased comfort for the inhabitants. The data obtained will be used to pinpoint specific areas where targeted interventions may optimize thermal performance, potentially leading to more substantial energy conservation and additional cost savings (e.g., Sp1 and Sp2 for G24--Figure 13). Comparative analysis of acquisition protocols revealed a critical dependence of thermal data colour representation on the initial acquisition point, attributed to the system's calibration for absolute colour values. Optimal colourimetric fidelity was achieved when the acquisition sequence commenced with a representative Thermal Building Element (TBE) exhibiting extreme thermal differentials relative to other system components. This methodology facilitated a precise colourimetric representation of both RGB and thermal data, resulting in accurate point cloud generation [31]. Terrestrial laser thermal scanning was used to assess the thermal performance of the student dormitory walls, complementing the initial aerial thermal survey of the roofs. The objective of terrestrial laser thermal scanning was to detect and analyse thermal performance and inefficiencies in dormitory walls by identifying thermal bridges, insulation gaps, and potential areas of energy loss that could not be fully captured from an aerial perspective. Structure-from-Motion (SfM) photogrammetric 3D data generation, reliant on optical imagery, exhibits inherent limitations. These limitations can be substantially mitigated through post-processing methodologies employing referenced datasets. Alternatively, laser-scanning-assisted image acquisition offers a potential pathway to eliminate these photogrammetric limitations entirely [32]. Figure 13: Thermal assessment of G24. For all Terrestrial Laser Scanning (TLS) operations, targets and scanning position registration are critical components for successful 3D modelling, as these aspects ensure the accuracy and comprehensiveness of the captured data, facilitating the creation of a detailed and precise 3D model of the scanned environment. Target registration involves placing artificial targets or recognising natural features in the scanning environment, which act as reference points during the data processing phase. These targets are used in the alignment and overlap process to bring together multiple scans with precision. The strategic placement of the targets was considered, as they should be visible from at least two different scanning positions to ensure robust registration. The considered targets covered the entire scanned area of interest, being uniformly distributed across the site. For each asset, multiple scanning stations were considered to ensure that all the details were captured, resulting in between 6 and 11 scanning stations for each asset. Figure 14 presents the scanning stations for the C8 student accommodation, as an example. The scanning positions (C8_1...C8_11) are determined by the need to cover the entire area of interest comprehensively, while each position should offer a clear view of a significant portion of the asses, minimizing occlusions and the so-called shadow areas.