## Materials and Methods
### Model-Driven Modelling
Model 1 was derived from the building footprint segmented using DSM (3D Basemaps: Segment building footprints using elevation). The model has an RMSE of 3.641, a mean C2M of 1.254 m, and a C2M standard deviation of 1.725 m. The problem of this model is its inability to divide the model's roof into elementary roofs (Figure 14b). This problem depends on the failure in segmenting the building footprint suitably (Figure 14a). Model 2 was derived from the building footprint segmented using point cloud with Lidar Rooftop Analysis by Whitebox Tools. The model has an RMSE of 1.867, a mean C2M of 0.237 m, and a C2M standard deviation of 0.813 m. Because the segmented building footprint is fragmented (Figure 14c), this produces a model with fractured and irregular roofs, which is difficult to use for practical purposes (Figure 14d). Model 3 was produced from the automatically segmented building footprint based on nadir image (ArcGis PRO: Segmentation). The model has an RMSE of 1.186, a mean C2M of 0.174 m, and a C2M standard deviation of 0.603 m. The problems of fragmentation and irregularities observed in model 2 are also observed in model 3. Model 4 was extracted directly from the building footprint available in Open Street Map (OSM) [49; 50; 51; 52; 53]. The model has an RMSE of 2.679, a mean C2M of 0.240 m, and a C2M standard deviation of 1.200 m. The building footprint does not report all internal patios (Figure 14g) and this absence is reflected in the extracted model 4 (Figure 14h). Model 5 was produced from a building footprint (Figure 14i) segmented using the OSM map as featured in 3D Basemaps (3D Basemaps: Split building footprints using features). The model has an RMSE of 2.060, a mean C2M of 0.266 m, and a C2M standard deviation of 1.040 m. Because model 5 can be considered as the union between model 1 and model 4, with this union it was possible to reconstruct some of the patios missing in model 4 (Figure 14j). Model 6 was generated from the building footprint segmented interactively based on the nadir image (Figure 14k) [12]. The model has an RMSE of 1.413, a mean C2M of 0.127 m, and a C2M standard deviation of 0.767 m. Model 6, with model 3, has the best combination of RMSE and C2M values, but some roofs were not modelled correctly by the software due to errors in the automatic recognition of the roof type. Compared to model 3, model 6 has no problems with fracturing and roof irregularities, and this makes model 6 better than model 3 (Figure 14l). Therefore, the editing phase was applied to model 6 and two interactive editing operations were performed:  
1. Building footprint correction based on DSM (3D Basemaps: Modify Roof Tools);
2. Parametric correction of the roofs through the modification of one or more fields of the attributes table (RooffForm, RoofDirAdjust, BldgHeight, EaveHeight). The corrected model 6 has an RMSE of 1.167 and was renamed \"model 7\". This new model was built as a solid in Autodesk Meshmixer (Autodesk Meshmixer: Make Solid) to merge the various elementary roofs together and recreate the composite roof of the structure. Subsequently, the model was textured in MeshLab like the tri-mesh model described in Section 2.3.3 (Figure 15).