# Massive Data Capture Approach for Modeling Existing Building Stocks
## 6 Conclusions  
Through methodical optimization of the main steps of existing building surveys, this paper contributes to advancing practical knowledge for conducting optimized surveys of existing building stocks by incorporating their urban context. It achieves this by defining a new approach, the main novelty of which is data preparation for 3D reconstruction, an optimized method that aims to move forward compared to previous proposals. The novel approach has proven successful in obtaining the BIM of the case study, which is a reference building of a cluster of school centers in need of refurbishment. The resulting BIM has the appropriate precision and timeframe for the rehabilitation of existing non-heritage buildings, includes the surroundings, and is georeferenced. The latest reference is essential for the usability of the resulting model in GIS software QGIS 3.34.4 to manage building stock. The approach combines three data-capturing technologies for the building exterior, which results in greater precision in the construction of the model. The novel approach has also been useful for geometric verification of the existing building. This is a novel application beyond the potential of similar existing models applied for surveying heritage buildings. Figure 10: Simulation of the urban-scale digital model of the clusters related to the case study. The main specific findings from developing and validating this approach are as follows:  
1. As expected, this project corroborates previous literature results. Laser scans (TLS) are the most precise, at the cost of having less coverage. HQP photogrammetry has good precision with medium coverage. Drone-captured HQPs or AFE improves the coverage, particularly in roofs, while the facade's coverage can be good enough using only TLS. Finally, adding TLS to HQPs, AFE, or the combination of both improves precision to the highest level. 2. As new developments, to the authors' best knowledge, video photogrammetry (AFE) has enough precision and the greatest coverage, and adding HQPs to AFE improves the precision to a high level. Regarding the data capture for similar case studies, the following conclusions are drawn:  
1. The combination of two techniques has the greatest advantages in precision and coverage. 2. Combining drones with mixed AFE and HQP technologies improves coverage without losing precision and is the most cost-effective solution for large datasets. 3. One technology enables the entire building to be covered. 4. Using drones results in cost reductions compared to TLS. 5. The flight time can be reduced by using AFE photogrammetry. In these cases, precision can be improved by the usage of TLS. This is crucial when there are limitations regarding the flight of drones due to legislation. The outcomes can provide valuable insights for conducting efficient, accurate surveys of existing buildings and utilizing standardized procedures that may facilitate the automation of larger-scale UAV-based photogrammetry workflows, thereby facilitating the generation of digital twins across various scales. In turn, this could enhance industry practices, public strategies, and future research endeavors in this domain. Furthermore, future investigations can use the proposed methodology to progress towards standardized procedures that strike a balance between data capturing and processing efforts and the quality of the reconstructed scene. This methodology has potential limitations due to the characteristics of the buildings for which it was developed. Further analysis is required to test or fully understand the potential limitations on other building types and their impact. In the case of applying the methodology to heritage case studies with complex geometries and occlusions, the improvement brought by this methodology could be less significant since detailed and specific data capture must be performed for those elements.