FILIPPA, Gianluca; CREMONESE, Edoardo; MIGLIAVACCA, Mirco; GALVAGNO, Marta; FORKEL, Matthias; WINGATE, Lisa; TOMELLERI, Enrico; MORRA DI CELLA, Umberto; RICHARDSON, Andrew D.

doi:10.1016/j.agrformet.2016.01.006

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CREMONESE, Edoardo
Environmental Protection Agency of Aosta Valley = Agenzia regionale protezione ambiante Valle d'Aosta [ARAP Valle Aosta]

MIGLIAVACCA, Mirco
Max Planck Institute for Biogeochemistry [MPI-BGC]

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Agricultural and Forest Meteorology. 2016, vol. 220, p. 141-150

Elsevier Masson

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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.< Réduire

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image analysis

community ecology

pixel-based analysis

phenology

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Phenopix: A R package for image-based vegetation phenology

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