Phenopix: A R package for image-based vegetation phenology
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作者:
Filippa, Gianluca
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Environm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, ItalyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Filippa, Gianluca
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Cremonese, Edoardo
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Environm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, ItalyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Cremonese, Edoardo
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Migliavacca, Mirco
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Max Planck Inst Biogeochem, Dept Biogeochem Integrat, D-07745 Jena, GermanyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Migliavacca, Mirco
[2
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Galvagno, Marta
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Environm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, ItalyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Galvagno, Marta
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Forkel, Matthias
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Max Planck Inst Biogeochem, Dept Biogeochem Integrat, D-07745 Jena, GermanyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Forkel, Matthias
[2
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Wingate, Lisa
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INRA, UMR ISPA, Bordeaux, FranceEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Wingate, Lisa
[3
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Tomelleri, Enrico
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Inst Appl Remote Sensing, EURAC, Bolzano, ItalyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Tomelleri, Enrico
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di Cella, Umberto Morra
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Environm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, ItalyEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
di Cella, Umberto Morra
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Richardson, Andrew D.
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Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USAEnvironm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
Richardson, Andrew D.
[5
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机构:
[1] Environm Protect Agcy Aosta Valley, ARPA Valle dAosta, Climate Change Unit, Aosta, Italy
In this paper we extensively describe new software available as a R package that allows for the extraction of phenological information from time-lapse digital photography of vegetation cover. The phenopix R package includes all steps in data processing. It enables the user to: draw a region of interest (ROI) on an image; extract red green and blue digital numbers (DN) from a seasonal series of images; depict greenness index trajectories; fit a curve to the seasonal trajectories; extract relevant phenological thresholds (phenophases); extract phenophase uncertainties. The software capabilities are illustrated by analyzing one year of data from a selection of seven sites belonging to the PhenoCam network (http://phenocam.sr.unh.edu/), including an unmanaged subalpine grassland, a tropical grassland, a deciduous needle-leaf forest, three deciduous broad-leaf temperate forests and an evergreen needle-leaf forest. One of the novelties introduced by the package is the spatially explicit, pixel-based analysis, which potentially allows to extract within-ecosystem or within-individual variability of phenology. We examine the relationship between phenophases extracted by the traditional ROI-averaged and the novel pixel-based approaches, and further illustrate potential applications of pixel based image analysis available in the phenopix R package. (C) 2016 Elsevier B.V. All rights reserved.