A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series

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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2019-04-17
Major/Subject
Mcode
Degree programme
Language
en
Pages
14
Series
FRONTIERS IN PLANT SCIENCE, Volume 10
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.
Description
Keywords
laser scanning, time series, structural dynamics, circadian rhythm, phenology, POINT CLOUDS, TREE MODELS, CANOPY STRUCTURE, LEAF GROWTH, STEM, RECONSTRUCTION, ARABIDOPSIS, QUANTIFICATION, MOVEMENTS, PHENOLOGY, Structural dynamics, Time series, Circadian rhythm, Phenology, Laser scanning
Citation
Puttonen , E , Lehtomäki , M , Litkey , P , Näsi , R , Feng , Z , Liang , X , Wittke , S , Pandzic , M , Hakala , T , Karjalainen , M & Pfeifer , N 2019 , ' A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series ' , FRONTIERS IN PLANT SCIENCE , vol. 10 , 486 . https://doi.org/10.3389/fpls.2019.00486