Investigating the capacity of dense point cloud photogrammetry to map low rise buildings

The aim of this project was to produce three dimensional dense point cloud data of a low rise building. To achieve this objective, an entry level Canon SLR digital camera was used together with a reasonably priced photogrammetry software package - PhotoScan. The Royal Tasmanian Botanical Gardens Conservatory building was selected to test the capabilities and the limitations of close range photogrammetry. The rugged stone walls and white-painted glass roof as well as the various retaining walls in close proximity, garden beds and upright vegetation set a series of challenges during image capturing. Several dense point cloud models were produced with high spatial resolution. The dense point clouds not only produced visually pleasing images on the screen but the georeferenced points constitute accurate fully three dimensional virtual models of the building and the surrounding area. A dense point cloud contains several millions of points. Each point possesses Easting/Northing and AHD values, several additional attributes and RGB spectral information. The dense point cloud data were stored in the ASPRS LAS format or the highly compressed LAZ binary file format. The LAS file format can be directly read by a wide range of professional and scientific software, therefore many existing methods and tools are available to further process the dense point cloud data. Although this project revolves around the use of digital imagery and PhotoScan photogrammetry software, the Leica Nova MS50 MultiStation was also employed to scan and map the area. MS50 also uses close range photogrammetry in order to assign spectral attributes to the scanned points. The dense point cloud data produced by the laser scanner which proved to be very similar in appearance, was also saved in LAS file format and post processed using the same methods as the point clouds produced using the camera. This project used the basic features of the LAStools and LISCAD software to post process the data of dense point cloud into a familiar format suitable for presentation to building industry professionals. The results of the project proved that it is feasible to map and post process dense point cloud data of man-made structures with the use of common digital camera imagery and readily available photogrammetry software.