Exploring Existing 3d Reconstruction Tools for the Generation of 3d City Models at Various Lod From a Single Data Source

Abstract

Abstract. The use of three-dimensional (3D) city models has increased in a wide range of applications beyond visualisation. However, generation and maintenance of 3D data comes at a high cost, time, and workload. The purpose of the generalisation where coarser versions are obtained from a source data is of great interest for National Mapping and Cadastral Agencies (NMCA), which would benefit obtaining multiple 3D versions of an area from a single source. The main aim of the exploration presented in this paper is to study the potential of downsizing point clouds as an approach to generate 3D city models at multiple levels of detail from a single source and evaluate the steps required to ensure the output is fit for real world applications from an NMCA context. While interesting results are obtained when testing with sample data, no software managed to semi-automatically reconstruct 3D model for buildings of rather complicated geometry.

Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data

“…For the efficient production of DTs, many researchers have focused on investigating methods and approaches concerning efficient workflows in 3D urban context reconstruction, visualization of the built environment, and related data. Muñumer Herrero et al [10] compare different methodologies and software packages for exploring the possibility of creating various levels of detail (LoDs) from a single data source. The methods used were TU Delft's 3Dfier (version 1.3.2) [6], ArcGIS API version 2.1.0 for Python version 3.0 (https://developers.arcgis.com/python/), and two different reconstruction processes, one called Polyfit version 1.5 [11] by Poux et al [12], and another called RANSAC [13].…”