Point Cloud Data Mining with HD Map Priors for making Synthetic Forest Datasets

dataset cite 0 Year 2025
source: Zenodo (CERN European Organization for Nuclear Research)
Abstract

Data from the article "Point Cloud Data Mining with HD Map Priors for making Synthetic Forest Datasets" by K. Karlauskas, J. Gelšvartas, P. Treigys (2025) Article: https://doi.org/10.1109/JSTARS.2025.3593827 Code repository: https://github.com/kasparas-k/pointcloud-tree-data-mining # Dataset contents 1. individual_trees.zip -- individual tree candidate point clouds, including erroneous or otherwise noisy segmentation results. The file `filtered_features.json` contains geometric features of all automatically extracted clusters, while `checked_features.json` contains geometric features only of a subset of visually vetted tree instances. 2. synthetic_scenes.zip -- synthetic forest scene *.laz point clouds with individual tree instance labels in the scalar field treeID 3. segmentation_test_output.zip -- output segmentation labels with various algorithms, refer to the original publication. 4. Data of individual tree locations in Tallinn and Warsaw acquired from https://www.openstreetmap.org/ is attached in the `openstreetmap` folder. The geolocation data from OpenStreetMap is licensed under ODBL https://opendatacommons.org/licenses/odbl/


Concepts :
Remote Sensing and LiDAR Applications
3D Surveying and Cultural Heritage
Tree Root and Stability Studies
dataset cite 0 Year 2025 source Zenodo (CERN European Organization for Nuclear Research)
SDGs
Life in Land
Citations by Year
YearCount
2025 0