# From Analogue to Digital Photogrammetry: Documentation of Padise Abbey in Two Different Time Stages
## 5 Comparison
The result could be a data for GIS and BIM systems [25]. On the other hand, point cloud is not a result intended for general public. Even though tools like plas.io, HexaLab, Potree, and Sketchfab bring the point clouds closer to the wider audience, it is necessary to have certain knowledge and tools to operate and interpret point clouds. Despite that fact, point cloud can offer an interesting comparison with the potential of gathering the semantic data automatically and semi-automatically. The point clouds generated by re-processing and by new survey were compared to each other by Cloud/Cloud distance method in CloudCompare [26] software. According to [27], both point clouds had to be pre-processed before Cloud/Cloud comparison. Both point clouds were filtered using statistical outlier removal function (S  
Figure 9: Comparison between states in 1991 and 2017 of the south wall of Padise Abbey: (**a**) an overlay of cropped orthophoto generated by re-processing (grey colors) and by new survey; (**b**) a drawing of stones. Yellow color indicates preserved stones, blue color indicates new stones after renovation. After the filtering, the point cloud of the new survey had a resolution of 1 point per ca. 2 cm\({}^{2}\) and the point cloud from re-processing had 1 point per ca. 0.6 cm\({}^{2}\). To use the point cloud of the new survey as the reference, we had to subsample the point cloud of the re-processing to have lower resolution (final resolution was 1 point per 3 cm\({}^{2}\)). From the result of comparison, it is possible to easily examine the changes between the states in 1991 and 2017, not only by visible matter but also by determination of differences. The comparison showed that 76.2% of points have a lower difference than 0.05 m. In respect to the accuracy of georeferencing of the model of the new survey, we considered these points as points belonging to the preserved stones. The rest of the points were considered as points belonging to the outcome of the renovation. The points with a difference under the threshold 0.05 m were overlayed to the orthophoto and the position of points were compared to the manually created boundary from the orthophoto (see Figure 10). The final chosen resolution of the reference point cloud (new survey point cloud) after filtering can have an impact on the result of the Cloud/Cloud comparison. To avoid that, we also created a mesh from the point cloud of the new survey. The mesh was used as reference in Cloud/Mesh comparison with point cloud of re-processing. A figure of 76.5% of the differences were under the chosen threshold of 0.05 m and we considered them also as points belonging to the preserved stones. The overlay of the points with orthophoto and manually created boundary were carried out. By eye, both overlays seem identical (for that reason, we present only overlay with Cloud/Cloud comparison in Figure 10). Both match with the boundary, which verifies the 0.05 m threshold (especially around the windows). The percentage of points under the threshold is very similar so we observed that even Cloud/Cloud comparison was relevant. For distinction between preserved and new stones, it was sufficient to use presented method. The topic of finding the semantic information from multitemporal data and Cloud/Cloud and Cloud/Mesh comparison encourages future development of advanced semi-automatic methods. By [28] were presented methods of change detection on depth maps of orthophotos generated based on the images captured in different time stages. One of the methods was comparing histograms of the depth maps and another method was based on subtracting of depth maps of orthophotos between each other. Methods for structural changes on cultural heritage objects were presented by [29].