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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.
Afiliação
  • Puttonen E; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Lehtomäki M; Department of Remote Sensing and Photogrammetry, Centre of Excellence in Laser Scanning Research, National Land Survey of Finland, Helsinki, Finland.
  • Litkey P; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Näsi R; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Feng Z; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Liang X; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Wittke S; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Pandzic M; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
  • Hakala T; Department of Built Environment, Aalto University, Espoo, Finland.
  • Karjalainen M; University of Novi Sad, BioSense Institute, Novi Sad, Serbia.
  • Pfeifer N; Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Helsinki, Finland.
Front Plant Sci ; 10: 486, 2019.
Article em En | MEDLINE | ID: mdl-31110511
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Plant Sci Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Plant Sci Ano de publicação: 2019 Tipo de documento: Article