TY - JOUR
T1 - Phenopix
T2 - A R package for image-based vegetation phenology
AU - Filippa, Gianluca
AU - Cremonese, Edoardo
AU - Migliavacca, Mirco
AU - Galvagno, Marta
AU - Forkel, Matthias
AU - Wingate, Lisa
AU - Tomelleri, Enrico
AU - Morra di Cella, Umberto
AU - Richardson, Andrew D.
N1 - Publisher Copyright:
© 2016 Elsevier B.V..
PY - 2016/4/15
Y1 - 2016/4/15
N2 - 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.
AB - 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.
KW - Community ecology
KW - Image analysis
KW - Phenology
KW - Pixel-based analysis
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U2 - 10.1016/j.agrformet.2016.01.006
DO - 10.1016/j.agrformet.2016.01.006
M3 - Article
AN - SCOPUS:84961386116
SN - 0168-1923
VL - 220
SP - 141
EP - 150
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
ER -