Title

Use of digital webcam images to track spring green-up in a deciduous broadleaf forest

Abstract

Understanding relationships between canopy structure and the seasonal dynamics of photosynthetic uptake of CO2 by forest canopies requires improved knowledge of canopy phenology at eddy covariance flux tower sites. We investigated whether digital webcam images could be used to monitor the trajectory of spring green-up in a deciduous northern hardwood forest. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Bartlett AmeriFlux site. Images were collected each day around midday. Red, green, and blue color channel brightness data for a 640 × 100-pixel region-of-interest were extracted from each image. We evaluated the green-up signal extracted from webcam images against changes in the fraction of incident photosynthetically active radiation that is absorbed by the canopy (f APAR), a broadband normalized difference vegetation index (NDVI), and the light-saturated rate of canopy photosynthesis (A max), inferred from eddy flux measurements. The relative brightness of the green channel (green %) was relatively stable through the winter months. A steady rising trend in green % began around day 120 and continued through day 160, at which point a stable plateau was reached. The relative brightness of the blue channel (blue %) also responded to spring green-up, although there was more day-to-day variation in the signal because blue % was more sensitive to changes in the quality (spectral distribution) of incident radiation. Seasonal changes in blue % were most similar to those in f APAR and broadband NDVI, whereas changes in green % proceeded more slowly, and were drawn out over a longer period of time. Changes in A max lagged green-up by at least a week. We conclude that webcams offer an inexpensive means by which phenological changes in the canopy state can be quantified. A network of cameras could offer a novel opportunity to implement a regional or national phenology monitoring program.

Publication Date

5-7-2007

Journal Title

Oecologia

Publisher

Springer

Digital Object Identifier (DOI)

10.1007/s00442-006-0657-z

Document Type

Article