Phenopix: A R package for image-based vegetation phenology

Research output: Contribution to journalResearch articleContributedpeer-review


  • Gianluca Filippa - , Environmental Protection Agency of Aosta Valley (Author)
  • Edoardo Cremonese - , Environmental Protection Agency of Aosta Valley (Author)
  • Mirco Migliavacca - , Max Planck Institute for Biogeochemistry (Author)
  • Marta Galvagno - , Environmental Protection Agency of Aosta Valley (Author)
  • Matthias Forkel - , Max Planck Institute for Biogeochemistry (Author)
  • Lisa Wingate - , INRAE - National Institute of Agricultural Research (Author)
  • Enrico Tomelleri - , EURAC Research (Author)
  • Umberto Morra di Cella - , Environmental Protection Agency of Aosta Valley (Author)
  • Andrew D. Richardson - , Harvard University (Author)


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
Pages (from-to)141-150
Number of pages10
JournalAgricultural and forest meteorology
Publication statusPublished - 15 Apr 2016
Externally publishedYes

External IDs

ORCID /0000-0003-0363-9697/work/142252092



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

Library keywords