five

Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation

收藏
DataCite Commons2026-04-30 更新2025-04-17 收录
下载链接:
https://heidata.uni-heidelberg.de/citation?persistentId=doi:10.11588/DATA/UUMEDI
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have additional attributes (Deviation, Reflectance, Amplitude, GpsTime, PointSourceId, NumberOfReturns, ReturnNumber). Before labeling, all point clouds were filtered by Deviation, discarding all points with a Deviation greater than 50. An ASCII file with tree species and tree positions (in ETRS89 / UTM zone 32N; EPSG:25832) is provided, which can be used to normalize and center the point clouds. <br><br> This dataset is intended to be used for training and validation of algorithms for semantic segmentation (leaf-wood separation) of TLS tree point clouds, as done by Esmorís et al. 2023 (Related Publication). <br><br> The point clouds are a subset of a larger dataset, which is available on PANGAEA (Weiser et al. 2022b, see Related Dataset). More details on data acquisition and processing, file formats, and quality assessments can be found in the corresponding data description paper (Weiser et al. 2022a, see Related Material).
提供机构:
heiDATA
创建时间:
2023-10-02
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作