A pipeline for automatic building reconstruction for Digital Twins in complex urban environments

Abstract. Automatic building reconstruction is a strategic component for creating urban Digital Twins (DTs), enabling the generation of accurate and interoperable Level of Detail 2 (LOD2) models. These models provide an essential standard for applications such as Geographic Information Systems (GIS), energy and hydraulic simulations, and urban planning. To address these needs, the MEDUSA (MEDiterraneo: Uso Sostenibile dell’Ambiente) project, promoted by the University of Salerno and funded by the Italian Space Agency (ASI), developed an innovative pipeline. The method was optimized to model areas with complex geometries and articulated roofs, utilizing the Amalfi Coast as a test area. The developed workflow is based on the City3D algorithm, integrating LiDAR (Light Detection And Ranging) data with building footprints derived from the Regional Topographic Database (RTDB). The process involves point cloud segmentation to isolate buildings and the generation of a Triangulated Irregular Network (TIN) mesh. Roof contours are identified using edge detection operators, simplified into polylines, and regularized using geometric constraints like parallelism and orthogonality to ensure LOD2 compliance. Finally, polygons are vertically extruded and optimized through the PolyFit framework, ensuring closed and topologically correct polygonal models. To overcome computational challenges and LiDAR data variability, significant improvements were introduced, including process parallelization, alignment with the Digital Terrain Model (DTM), and batch management of GeoJSON files. These enhancements successfully increased the pipeline's robustness and efficiency. The enriched pipeline produces high-quality LOD2 models, laying a solid foundation for next-generation urban modeling capable of meeting the scalability and interoperability requirements of future smart cities.