Automatic Building Vectorization from Photogrammetric Point Clouds for GIS-based Spatial Analysis

Abstract

Photogrammetry has played an important 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 produced 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 ArcGIS Pro software. The study achieved a high accuracy in the classification process and automatic vectorization. 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.

Keywords

• Photogrammetry
• GIS
• Point Cloud
• Classification
• UAV

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