LiDAR-Based Tree Models for Braunschweig, Germany (2019)

EN: <p>This dataset provides detailed tree models for Braunschweig, Germany, derived from airborne LiDAR point clouds collected in February 2019.<br>
The data processing follows a <a href="https://doi.org/10.5281/zenodo.7692182">comprehensive workflow for mapping and 3D modeling of urban forests</a>.<br>
It uses an object‑based data‑fusion approach that integrates multispectral aerial imagery and a semantic 3D building model to classify and model individual trees with high accuracy and consistency.<br>
The dataset covers all vegetation over 2 m in height, including trees and shrubs, and includes four key products:</p>

<ul>
<li><strong>Canopy Height Model (CHM):</strong><br>
The CHM provides area‑wide tree canopy heights through a high‑resolution raster layer (0.5 m cell size) mapping the height of the upper crown layer above the underlying ground.</li>

<li><strong>Parameterized Tree Positions:</strong><br>
The Parameterized Tree Positions provide the location of all detected trees, with geometric attributes such as tree height and crown diameter derived for each.</li>

<li><strong>Parameterized Tree Crowns:</strong><br>
The Parameterized Tree Crowns provide the spatial extent of individual crowns as 2D convex‑hull polygons around all tree points.</li>

<li><strong>Semantic 3D Tree Models:</strong><br>
The Semantic 3D Tree Models provide reconstructed tree crowns modeled using geometric primitives, corresponding to CityGML Level of Detail (LoD) 2, with individual parameters determined for realistic volume replication.</li>
</ul>

<p>These products support urban forestry analysis, ecological research, city planning, and 3D visualization by providing standardized, high‑resolution representations of tree canopy heights, locations, crown extents, and three‑dimensional structures. The CHM enables fine‑scale assessment of canopy structure and ecosystem services; the parameterized tree positions and crowns serve as a comprehensive, automated inventory of individual trees; and the semantic 3D tree models integrate seamlessly into CityGML environments for enriched visualizations and spatial simulations.</p>