Volume XLII-4/W10 | Copyright
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W10, 223-230, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W10-223-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Sep 2018

12 Sep 2018

INTEGRATION OF SEMANTIC 3D CITY MODELS AND 3D MESH MODELS FOR ACCURACY IMPROVEMENTS OF SOLAR POTENTIAL ANALYSES

B. Willenborg1, M. Pültz2, and T. H. Kolbe1 B. Willenborg et al.
  • 1Chair of Geoinformatics, Technical University of Munich (TUM), 80333 Munich, Germany
  • 2Technical University of Munich (TUM), 80333 Munich, Germany

Keywords: Semantic 3D city models, 3D mesh models, solar potential analysis, CityGML, accuracy assesment

Abstract. High-resolution 3D mesh models are an inexpensive and increasingly available data source for 3D models of cities and landscapes of high visual quality and rich geometric detail. However, because of their simple data structure, their analytic capabilites are limited. Semantic 3D city model contain rich thematic information and are well suited for analytics due to their deeply structured semantic data model. In this work an approach for the integration of semantic 3D city models with 3D mesh models is presented. The method is based on geometric distance measures between mesh triangles and semantic surfaces and a region growing approach using plane fitting. The resulting semantic segmentation of mesh triangles is stored in a CityGML data set, to enrich the semantic model with an additional detailed geometric representation of its surfaces and a broad range of unrepresented features like technical building installations, balconies, dormers, chimneys, and vegetation. The potential of the approach is demonstrated on the example of a solar potential analysis, which estimation quality is significantly improved due to the mesh integration. The impact of the method is quantified on a case study using open data from the city of Helsinki.

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