DOKUMENTASI DIGITAL MODEL CITYGML BANGUNAN LOD2+ MENGGUNAKAN DATA GEOSLAM

• Main Author: Nuraswiputri, Endah
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/50645
• Institution: Institut Teknologi Bandung

Three-dimensional (3D) digital documentation of buildings can be used for many applications, such as navigation in buildings, mitigation, building evaluation and for 3D cadastre. The building 3D digital model can refer to the CityGML data structure which has a level of detail from 0 to 4. The level of detail made based on the needs of the model. There are many data collection methods used for 3D documentation, one of which is the SLAM method. SLAM itself means Localization and Simultaneous Mapping. In this final project, documentation of 3D buildings is carried out using the SLAM 3D method and then used for modeling CityGML buildings with LoD2+ level of detail. LoD2 + is a building model with building exterior geometry in the form of empty roof and facade details, as well as the indoor geometry of the building in the form of a 3D polygon of the facade of the room. The data that will be used are the building interior point cloud data and building exterior data. For building interior point cloud data, acquired using GeoSLAM, while for building exterior data, extruded data from KOICA building roof data are used, where the data already has CityGML format. In addition to the second data that came, there was IFC data for the KOICA building. This data is used as a reference for interior data in registering process. The point clouds in the interior data are then used as input for the creation of a three-dimensional model of the building (3D polygon). PolyFit software is used to model buildings in three dimensions. PolyFit processes point cloud data into planar segments which are then used as a reconstructed model. After that, the transformation and merging of 3D models were carried out by using the point-pair and manual method in CloudCompare software. The three-dimensional models are then classified based on their semantics to construct the CityGML LoD2+ building model. This process is done automatically in the existing programs. This final result is expected to be a reference in the building's three-dimensional modeling model in the future.