INTEGRATION OF 3D OBJECTS AND TERRAIN FOR 3D MODELLING SUPPORTING THE DIGITAL TWIN

• Published in: ISPRS annals of the photogrammetry, remote sensing and spatial information sciences Vol. IV-4/W8; pp. 147 - 154
• Main Authors: Yan, J., Zlatanova, S., Aleksandrov, M., Diakite, A. A., Pettit, C.
• Format: Journal Article
• Language: English
• Published: Gottingen Copernicus GmbH 2019; Copernicus Publications
• Subjects: Architectural elements; Buildings; Cities; Datasets; Digital twins; Image reconstruction; Military communications; Military operations; Planning; Terrain models; Three dimensional models; Tourism; Two dimensional models; Urban planning; Water management
• ISSN: 2194-9050; 2194-9042; 2194-9050
• DOI: 10.5194/isprs-annals-IV-4-W8-147-2019

3D modelling of precincts and cities has significantly advanced in the last decades, as we move towards the concept of the Digital Twin. Many 3D city models have been created but a large portion of them neglect representing terrain and buildings accurately. Very often the surface is either considered planar or is not represented. On the other hand, many Digital Terrain Models (DTM) have been created as 2.5D triangular irregular networks (TIN) or grids for different applications such as water management, sign of view or shadow computation, tourism, land planning, telecommunication, military operations and communications. 3D city models need to represent both the 3D objects and terrain in one consistent model, but still many challenges remain. A critical issue when integrating 3D objects and terrain is the identification of the valid intersection between 2.5D terrain and 3D objects. Commonly, 3D objects may partially float over or sink into the terrain; the depth of the underground parts might not be known; or the accuracy of data sets might be different. This paper discusses some of these issues and presents an approach for a consistent 3D reconstruction of LOD1 models on the basis of 3D point clouds, DTM, and 2D footprints of buildings. Such models are largely used for urban planning, city analytics or environmental analysis. The proposed method can be easily extended for higher LODs or BIM models.