CedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests
2026-08-31 • Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
AI summaryⓘ
The authors created a detailed dataset called CedarCypress3D, which includes 3D scans of Japanese cedar and cypress trees taken by drones using a technology called LiDAR. They carefully matched these drone scans with measurements from field surveys and also included ground-based LiDAR scans for some areas. This dataset helps researchers develop and test computer methods to identify and separate individual trees and their parts in forest scans. It is especially useful for studying planted forests in temperate regions and is publicly available for others to use.
LiDARUnmanned Aerial Vehicle (UAV)Point CloudIndividual Tree SegmentationSemantic SegmentationTerrestrial LiDARForest InventoryCryptomeria japonicaChamaecyparis obtusaDataset Annotation
Authors
Katsuto Shimizu, Fumiaki Kitahara, Tomohiro Nishizono, Hideki Saito, Masayoshi Takahashi, Shingo Obata, Shunsuke Tei, Naoyuki Furuya, Tomoya Goto, Eiji Kodani, Yusuke Yamada
Abstract
Individual tree measurements derived from Light Detection and Ranging (LiDAR) mounted on Unmanned Aerial Vehicles (UAV) provide valuable information for forest inventory, ecosystem monitoring, and sustainable forest management. Recent advancements in machine learning have increased the demand for annotated datasets to develop and evaluate point cloud-based approaches, especially for individual tree segmentation. However, publicly available annotated UAV-LiDAR datasets in temperate forests are limited. In this article, we present CedarCypress3D, a manually annotated UAV-LiDAR dataset collected in Japanese cedar (Cryptomeria japonica) and Japanese cypress (Chamaecyparis obtusa) plantations in Japan. The dataset consists of UAV-LiDAR point clouds and field survey measurements from 34 circular plots across two sites with different topographic characteristics, along with terrestrial LiDAR point clouds available for a subset of 22 plots. A total of 1,627 trees were measured in the census field survey and manually annotated to match the corresponding trees in the UAV-LiDAR point clouds. For the subset of plots with terrestrial LiDAR data, semantic labels (i.e., stem and non-stem) were additionally assigned to tree points in the UAV-LiDAR data. CedarCypress3D provides high-quality annotated UAV-LiDAR data for developing and evaluating individual tree instance segmentation and semantic segmentation methods in temperate planted forests. The dataset can also support research on tree attribute prediction and multi-platform LiDAR analysis. The dataset is publicly available at https://doi.org/10.5281/zenodo.22168721.