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Plot-level wood-leaf separation for terrestrial laser scanning point clouds

Citation

Wan, Peng; Zhang, Wuming; Jin, Shuangna (2021), Plot-level wood-leaf separation for terrestrial laser scanning point clouds, Dryad, Dataset, https://doi.org/10.5061/dryad.rfj6q5799

Abstract

With the increasing use of terrestrial laser scanning (TLS) technology in the field of forest ecology, wood-leaf separation for TLS point clouds of forest plots has attracted a large number of studies. This dataset was open to the public for the developing, testing and comparision of the wood-leaf separation methods for TLS data. The dataset was collected from three forest plots of different stem density, topography and tree species, i.e., a white birch (Betula papyrifera) plot, a Dahurian larch (Larix gmelinii) plot and a Chinese scholar tree (Styphnolobium japonicum) plot. The wood and leaf points were classified manually, which can be as the reference for method validation.

Methods

The TLS datasets were collected in Northern China. The WB plot is a 15 m × 30 m that includes 21 white birches on a slope of approximately 22 degrees. The DL plot is 15 m × 15 m and includes 15 trees on flat terrain. The CST plot is 30 m × 30 m and includes 37 trees on flat terrain. 

The TLS datasets were collected in July 2018 by using a Riegl VZ-1000 (Riegl GmbH, Horn, Austria) terrestrial laser scanner. The scan angle resolution was 0.03°, and the vertical and horizontal scanning ranges were 30°-130° and 0°-360°, respectively. In each sample plot, five to seven scans were implemented at the centre and the periphery of the rectangular plots. The scans were registered together using the RiSCAN Pro software package (Riegl GmbH, Horn, Austria). The registered point clouds were clipped to exclude trees outside each rectangular plot.

Usage Notes

Please contact wanpeng@mail.crsri.cn if have any questions.

Funding

National Natural Science Foundation of China, Award: 41671414

National Natural Science Foundation of China, Award: 41971380

National Natural Science Foundation of China, Award: 42001374