Leaf and wood classification framework for terrestrial LiDAR point clouds: Simulated data validation dataset

Name: Leaf and wood classification framework for terrestrial LiDAR point clouds: Simulated data validation dataset
Creator: CSIRO Land and Water, Black Mountain, 2601, ACT, Australia; Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom; NERC National Centre for Earth Observation, Leicester, UK; Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom
Published: 2018-07-31T00:00:00+08:00

Zenodo2018-07-31 更新2026-04-07 收录

地面LiDAR点云分类

叶片与木材区分

数据链接：

https://zenodo.org/record/1324158 数据链接链接失效反馈

官方服务：

资源简介：

Set of 200 3D point clouds used in the validation of "Leaf and wood classification framework for terrestrial LiDAR point clouds". This dataset is a collection of point clouds simulated by a Monte-Carlo ray tracing (librat) using four 3D tree models from the fourth phase RAMI exercise (Widlowski et al, 2015).

提供机构：

CSIRO Land and Water, Black Mountain, 2601, ACT, Australia; Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom; NERC National Centre for Earth Observation, Leicester, UK; Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom

创建时间：

2018-07-31

Leaf and wood classification framework for terrestrial LiDAR point clouds: Simulated data validation dataset

资源简介：

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