Literature DB >> 30415486

Tracking seasonal rhythms of plants in diverse ecosystems with digital camera imagery.

Andrew D Richardson1,2.   

Abstract

Contents Summary I. Introduction II. Evolving modes of phenological study III. The phenocam approach IV. Applications of the phenocam method V. Looking forward Acknowledgements References
SUMMARY: Global change is shifting the seasonality of vegetation in ecosystems around the globe. High-frequency digital camera imagery, and vegetation indices derived from that imagery, is facilitating better tracking of phenological responses to environmental variation. This method, commonly referred to as the 'phenocam' approach, is well suited to several specific applications, including: close-up observation of individual organisms; long-term canopy-level monitoring at individual sites; automated phenological monitoring in regional-to-continental scale observatory networks; and tracking responses to experimental treatments. Several camera networks are already well established, and some camera records are a more than a decade long. These data can be used to identify the environmental controls on phenology in different ecosystems, which will contribute to the development of improved prognostic phenology models.
© 2018 The Author. New Phytologist © 2018 New Phytologist Trust.

Entities:  

Keywords:  green chromatic coordinate; near surface remote sensing; phenocam; phenology; repeat photography; time lapse photography; vegetation index

Mesh:

Year:  2018        PMID: 30415486     DOI: 10.1111/nph.15591

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  5 in total

1.  Deep Learning in Plant Phenological Research: A Systematic Literature Review.

Authors:  Negin Katal; Michael Rzanny; Patrick Mäder; Jana Wäldchen
Journal:  Front Plant Sci       Date:  2022-03-17       Impact factor: 6.627

2.  Peak radial growth of diffuse-porous species occurs during periods of lower water availability than for ring-porous and coniferous trees.

Authors:  Loïc D'Orangeville; Malcolm Itter; Dan Kneeshaw; J William Munger; Andrew D Richardson; James M Dyer; David A Orwig; Yude Pan; Neil Pederson
Journal:  Tree Physiol       Date:  2022-02-09       Impact factor: 4.196

3.  Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset.

Authors:  Bijan Seyednasrollah; Adam M Young; Koen Hufkens; Tom Milliman; Mark A Friedl; Steve Frolking; Andrew D Richardson
Journal:  Sci Data       Date:  2019-10-22       Impact factor: 8.501

4.  PhenoCams for Field Phenotyping: Using Very High Temporal Resolution Digital Repeated Photography to Investigate Interactions of Growth, Phenology, and Harvest Traits.

Authors:  Helge Aasen; Norbert Kirchgessner; Achim Walter; Frank Liebisch
Journal:  Front Plant Sci       Date:  2020-06-18       Impact factor: 6.627

5.  Seasonal variation in the canopy color of temperate evergreen conifer forests.

Authors:  Bijan Seyednasrollah; David R Bowling; Rui Cheng; Barry A Logan; Troy S Magney; Christian Frankenberg; Julia C Yang; Adam M Young; Koen Hufkens; M Altaf Arain; T Andrew Black; Peter D Blanken; Rosvel Bracho; Rachhpal Jassal; David Y Hollinger; Beverly E Law; Zoran Nesic; Andrew D Richardson
Journal:  New Phytol       Date:  2020-12-01       Impact factor: 10.323

  5 in total

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