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| Format: | Recurso digital |
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| Veröffentlicht: |
Zenodo
2025
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| Online-Zugang: | https://doi.org/10.5281/zenodo.17750604 |
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Inhaltsangabe:
- <p>Dataset to test the occlusion mapping tool OccPy available <a href="https://github.com/dkueken/OccPy" target="_blank" rel="noopener">here</a>. Data acquired using mobile (MLS), terrestrial (TLS), and drone-based (ULS) laser scanning from a temperate forest close to Zurich Switzerland are provided. Data has been greatly filtered and subsampled to reduce data size to be used in tutorials and package testing.</p> <p>We suggest to use this data for the following bounding box, as also used in the tutorial notebooks found in the <a href="https://github.com/dkueken/OccPy" target="_blank" rel="noopener">code repository</a>: </p> <p>min_x: 2676515<br>min_y: 1246063<br>min_z: 545<br>max_x: 2676525<br>max_y: 1246113<br>max_z: 590</p> <p>TLS data was acquired using a Riegl VZ400i under leaf-off conditions in winter 2023</p> <p>MLS data was acquired using a GeoSLAM ZebHorizon handheld scannin under leaf-on conditions in summer 2025</p> <p>ULS data was acquired using a Riegl miniVUX-3 mounted on a DJI Matrice M600pro under leaf-on conditions in summer 2024</p> <p>Both point clouds (.laz) and scan position or trajectory information are provided. Additionally a reference digital terrain (DTM) and surface (DSM) model are provided. </p> <p> </p>