Siirry päänavigointiin Siirry hakuun Siirry pääsisältöön

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

  • Eetu Puttonen*
  • , Matti Lehtomäki
  • , Paula Litkey
  • , Roope Näsi
  • , Ziyi Feng
  • , Xinlian Liang
  • , Samantha Wittke
  • , Milos Pandzic
  • , Teemu Hakala
  • , Mika Karjalainen
  • , Norbert Pfeifer
  • *Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

22 Sitaatiot (Scopus)
234 Lataukset (Pure)

Abstrakti

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.

AlkuperäiskieliEnglanti
Artikkeli486
Sivumäärä14
JulkaisuFrontiers in Plant Science
Vuosikerta10
DOI - pysyväislinkit
TilaJulkaistu - 17 huhtik. 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

This work was supported in part by the Academy of Finland Center of Excellence in Laser Scanning Research (No. 272195/292735/307362) and the Academy of Finland's research projects New Applications for Ubiquitous Multi- and Hyperspectral Mobile Mapping Systems (No. 265949/292757), Integration of large multisource point cloud and image datasets for adaptive map updating (No. 295047), and Upscaling of carbon intake and water balance models of individual trees to wider areas with short interval laser scanning time series (No. 316096).

Sormenjälki

Sukella tutkimusaiheisiin 'A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Siteeraa tätä