Literature DB >> 18288519

Monitoring plant phenology using digital repeat photography.

Michael A Crimmins1, Theresa M Crimmins.   

Abstract

Repeated observations of plant phenology have been shown to be important indicators of global change. However, capturing the exact date of key events requires daily observations during the growing season, making phenologic observations relatively labor intensive and costly to collect. One alternative to daily observations for capturing the dates of key phenologic events is repeat photography. In this study, we explored the utility of repeat digital photography for monitoring phenologic events in plants. We provide an illustration of this approach and its utility by placing observations made using repeat digital imagery in context with local meteorologic and edaphic variables. We found that repeat photography provides a reliable, consistent measurement of phenophase. In addition, digital photography offers advantages in that it can be mathematically manipulated to detect and enhance patterns; it can classify objects; and digital photographs can be archived for future analysis. In this study, an estimate of greenness and counts of individual flowers were extracted by way of mathematic algorithms from the photo time series. These metrics were interpreted using meteorologic measurements collected at the study site. We conclude that repeat photography, coupled with site-specific meteorologic measurements, could greatly enhance our understanding environmental triggers of phenologic events. In addition, the methods described could easily be adopted by citizen scientists and the general public as well as professionals in the field.

Mesh:

Year:  2008        PMID: 18288519     DOI: 10.1007/s00267-008-9086-6

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  11 in total

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7.  Photographs and herbarium specimens as tools to document phenological changes in response to global warming.

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Authors:  Elsa E Cleland; Nona R Chiariello; Scott R Loarie; Harold A Mooney; Christopher B Field
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9.  Plant development scores from fixed-date photographs: the influence of weather variables and recorder experience.

Authors:  T H Sparks; K Huber; P J Croxton
Journal:  Int J Biometeorol       Date:  2006-01-10       Impact factor: 3.787

10.  Use of digital webcam images to track spring green-up in a deciduous broadleaf forest.

Authors:  Andrew D Richardson; Julian P Jenkins; Bobby H Braswell; David Y Hollinger; Scott V Ollinger; Marie-Louise Smith
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  11 in total

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Journal:  Ambio       Date:  2011-09       Impact factor: 5.129

2.  Photographic assessment of temperate forest understory phenology in relation to springtime meteorological drivers.

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3.  Five years of phenological monitoring in a mountain grassland: inter-annual patterns and evaluation of the sampling protocol.

Authors:  Gianluca Filippa; Edoardo Cremonese; Marta Galvagno; Mirco Migliavacca; Umberto Morra di Cella; Martina Petey; Consolata Siniscalco
Journal:  Int J Biometeorol       Date:  2015-05-03       Impact factor: 3.787

4.  Matching the best viewing angle in depth cameras for biomass estimation based on poplar seedling geometry.

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6.  Investigating Surface and Near-Surface Bushfire Fuel Attributes: A Comparison between Visual Assessments and Image-Based Point Clouds.

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7.  Studying plant-pollinator interactions in a changing climate: A review of approaches.

Authors:  Diane L Byers
Journal:  Appl Plant Sci       Date:  2017-06-28       Impact factor: 1.936

8.  An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

Authors:  Unseok Lee; Sungyul Chang; Gian Anantrio Putra; Hyoungseok Kim; Dong Hwan Kim
Journal:  PLoS One       Date:  2018-04-27       Impact factor: 3.240

9.  An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture.

Authors:  Michael A Beck; Chen-Yi Liu; Christopher P Bidinosti; Christopher J Henry; Cara M Godee; Manisha Ajmani
Journal:  PLoS One       Date:  2020-12-17       Impact factor: 3.240

10.  Very-high-resolution time-lapse photography for plant and ecosystems research.

Authors:  Mary H Nichols; Janet C Steven; Randy Sargent; Paul Dille; Joshua Schapiro
Journal:  Appl Plant Sci       Date:  2013-09-02       Impact factor: 1.936

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