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

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A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series. / Puttonen, Eetu; Lehtomäki, Matti; Litkey, Paula; Näsi, Roope; Feng, Ziyi; Liang, Xinlian; Wittke, Samantha; Pandzic, Milos; Hakala, Teemu; Karjalainen, Mika; Pfeifer, Norbert.

In: FRONTIERS IN PLANT SCIENCE, Vol. 10, 486, 17.04.2019.

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Puttonen, Eetu ; Lehtomäki, Matti ; Litkey, Paula ; Näsi, Roope ; Feng, Ziyi ; Liang, Xinlian ; Wittke, Samantha ; Pandzic, Milos ; Hakala, Teemu ; Karjalainen, Mika ; Pfeifer, Norbert. / A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series. In: FRONTIERS IN PLANT SCIENCE. 2019 ; Vol. 10.

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@article{58a3b52098694c85afff5557032c1a90,
title = "A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series",
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.",
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",
author = "Eetu Puttonen and Matti Lehtom{\"a}ki and Paula Litkey and Roope N{\"a}si and Ziyi Feng and Xinlian Liang and Samantha Wittke and Milos Pandzic and Teemu Hakala and Mika Karjalainen and Norbert Pfeifer",
year = "2019",
month = "4",
day = "17",
doi = "10.3389/fpls.2019.00486",
language = "English",
volume = "10",
journal = "FRONTIERS IN PLANT SCIENCE",
issn = "1664-462X",
publisher = "Frontiers Research Foundation",

}

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TY - JOUR

T1 - A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series

AU - Puttonen, Eetu

AU - Lehtomäki, Matti

AU - Litkey, Paula

AU - Näsi, Roope

AU - Feng, Ziyi

AU - Liang, Xinlian

AU - Wittke, Samantha

AU - Pandzic, Milos

AU - Hakala, Teemu

AU - Karjalainen, Mika

AU - Pfeifer, Norbert

PY - 2019/4/17

Y1 - 2019/4/17

N2 - 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.

AB - 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.

KW - laser scanning

KW - time series

KW - structural dynamics

KW - circadian rhythm

KW - phenology

KW - POINT CLOUDS

KW - TREE MODELS

KW - CANOPY STRUCTURE

KW - LEAF GROWTH

KW - STEM

KW - RECONSTRUCTION

KW - ARABIDOPSIS

KW - QUANTIFICATION

KW - MOVEMENTS

KW - PHENOLOGY

KW - Structural dynamics

KW - Time series

KW - Circadian rhythm

KW - Phenology

KW - Laser scanning

UR - http://www.scopus.com/inward/record.url?scp=85067354351&partnerID=8YFLogxK

U2 - 10.3389/fpls.2019.00486

DO - 10.3389/fpls.2019.00486

M3 - Article

VL - 10

JO - FRONTIERS IN PLANT SCIENCE

JF - FRONTIERS IN PLANT SCIENCE

SN - 1664-462X

M1 - 486

ER -

ID: 33496569