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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 141-150 |
| Number of pages | 10 |
| Journal | Agricultural and Forest Meteorology |
| Volume | 220 |
| DOIs | |
| State | Published - Apr 15 2016 |
| Externally published | Yes |
Keywords
- Community ecology
- Image analysis
- Phenology
- Pixel-based analysis
ASJC Scopus subject areas
- Forestry
- Global and Planetary Change
- Agronomy and Crop Science
- Atmospheric Science
Fingerprint
Dive into the research topics of 'Phenopix: A R package for image-based vegetation phenology'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS