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Published January 16, 2023 | Version v 1.0
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Semantic 3D Tree Model Dresden 2017

  • 1. Leibniz Institute of Ecological Urban and Regional Development (IOER)


  • 1. Leibniz Institute of Ecological Urban and Regional Development (IOER)
  • 2. Technische Universität Dresden, Institute for Cartography


The semantic 3D tree model contains reconstructed tree crowns within the City of Dresden (Germany). Area-wide availability of such models and their integration into semantic 3D city models facilitates enriched visualizations of urban areas as well as 3D spatial modeling that simulates the interaction of trees with buildings and the built environment.

The individual tree crowns were modeled using geometric primitives and correspond to the CityGML Level of Detail (LoD) 2. Individual modeling parameters were determined for each tree aiming for a realistic volume replication. LiDAR data from a survey in the year 2017 were used to parameterize the tree crowns. Tree crowns were modeled via ellipsoids fitted to crown extent, cylinders were used for trunk representation. The framework for segmenting individual trees in the LiDAR point cloud and for modeling individual tree crowns via geometric primitives is described in this article.

The tree models are available as CityGML files in the coordinate system ETRS89/UTM zone 33 (EPSG: 25833). The dataset was divided into tiles. The tile number results from the coordinate of the lower left corner in the coordinate reference system.

The source data used was made freely available by the “Landesamt für Geobasisinformation Sachsen” (GeoSN) under the license "Data license Germany - attribution - Version 2.0" and can be downloaded under the following links:
3D Building Model:
Aerial Imagery:


The City of Dresden supported generation and validation of the dataset by providing the municipal tree inventory. The research contributed to the project "Standard-BIPV-System" (FKZ: 03EE1061C) funded by the German Federal Ministry for Economic Affairs and Climate Action.


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Is supplement to
Journal article: 10.1016/j.ufug.2022.127637 (DOI)