Publications

Filippa, G; Cremonese, E; Migliavacca, M; Galvagno, M; Forkel, M; Wingate, L; Tomelleri, E; di Cella, UM; Richardson, AD (2016). Phenopix: A R package for image-based vegetation phenology. AGRICULTURAL AND FOREST METEOROLOGY, 220, 141-150.

Abstract
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.

DOI:
10.1016/j.agrformet.2016.01.006

ISSN:
0168-1923