Phenopix: A R package for image-based vegetation phenology

Gianluca Filippa, Edoardo Cremonese, Mirco Migliavacca, Marta Galvagno, Matthias Forkel, Lisa Wingate, Enrico Tomelleri, Umberto Morra di Cella, Andrew D. Richardson

Research output: Contribution to journalArticlepeer-review

137 Scopus citations


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 (, 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.

Original languageEnglish (US)
Pages (from-to)141-150
Number of pages10
JournalAgricultural and Forest Meteorology
StatePublished - Apr 15 2016
Externally publishedYes


  • Community ecology
  • Image analysis
  • Phenology
  • Pixel-based analysis

ASJC Scopus subject areas

  • Forestry
  • Global and Planetary Change
  • Agronomy and Crop Science
  • Atmospheric Science


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