Abstract
Terrestrial Laser Scanning (TLS) can be used to monitor plant dynamics with a frequency of several times per hour and with sub-centimeter accuracy, regardless of external lighting conditions. TLS point cloud time series measured at short intervals produce large quantities of data requiring fast processing techniques. These must be robust to the noise inherent in point clouds. This study presents a general framework for monitoring circadian rhythm in plant movements from TLS time series. Framework performance was evaluated using TLS time series collected from two Norway maples (Acer platanoides) and a control target, a lamppost. The results showed that the processing framework presented can capture a plant's circadian rhythm in crown and branches down to a spatial resolution of 1 cm. The largest movements in both Norway maples were observed before sunrise and at their crowns' outer edges. The individual cluster movements were up to 0.17 m (99th percentile) for the taller Norway maple and up to 0.11 m (99th percentile) for the smaller tree from their initial positions before sunset.
Highlights
Terrestrial Laser Scanning (TLS) measures its surrounding 3D environment using a dense point cloud
The presented method improves the monitoring performance compared with the earlier studies of Puttonen et al (2016) and Zlinszky et al (2017), which focus on short interval TLS point cloud uses
Terrestrial laser scanning time series represent a new approach for the study of circadian rhythm dynamics in plant sciences and are increasingly utilized in experimental settings
Summary
Terrestrial Laser Scanning (TLS) measures its surrounding 3D environment using a dense point cloud. It has become a staple in several research fields, including forest sciences (Dassot et al, 2011; Liang et al, 2016), landslide monitoring (Jaboyedoff et al, 2012), building change detection and deformation monitoring (Mukupa et al, 2017), and glaciology (Deems et al, 2013). Objects dozens of meters from the scanner can be mapped with sub-centimeter-level spatial resolution in minutes. This enables fast and accurate digitization of static scenes, both day and night. Compared with other terrestrial point cloud sources (e.g., image-based and personal laser scanning), TLS has the highest digitization accuracy and a unique capability of delineating crown structure (Liang et al, 2015)
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