Automatic Building Vectorization from Photogrammetric Point Clouds for GIS-based Spatial Analysis
Tolga Bozkurt, Muhammed Enes Atik, Zaide DuranPhotogrammetry has played an essential role in creating visually interesting three-dimensional (3D) models thanks to unmanned aerial vehicle (UAV) images in recent years. Photogrammetry and GIS are widely used together to produce and analyze 3D models. This study successfully created 3D models of buildings using photogrammetry and transferred them to GIS for analysis. UAVs were utilized to capture images, which were then processed to generate a dense point cloud. The point cloud was classified using rule-based classification. Buildings were vectorized and textured, and the resulting models were analyzed in commercial GIS software. The study proposed the classification process and automatic vectorization of buildingsin the photogrammetric point clouds. In the study, buildings were classified with 90% accuracy, and the obtained building point clouds were vectorized and transferred to a GIS environment. The use of UAVs expedited data collection and improved data quality, while the detailed analysis of the point enabled precise analysis for many applications such as urban planning and land management. The integration of building models into GIS facilitated more accurate and efficient work processes.