Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery: A new, publicly-available dataset

Abstract:

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is highly sensitive to climate change and variability, and is thus a key aspect of global change ecology.

The goal of the PhenoCam network is to serve as a long-term, continental-scale, phenological observatory. The network uses repeat digital photography—images captured using conventional, visible-wavelength, automated digital cameras—to characterize vegetation phenology in diverse ecosystems across North America and around the world.

At present, imagery from over 200 research sites, spanning a wide range of ecoregions, climate zones, and plant functional types, is currently being archived and processed in near-real-time through the PhenoCam project web page (http://phenocam.sr.unh.edu/). Data derived from PhenoCam imagery have been previously used to evaluate satellite phenology products, to constrain and test new phenology models, to understand relationships between canopy phenology and ecosystem processes, and to study the seasonal changes in leaf-level physiology that are associated with changes in leaf color.

I will describe a new, publicly-available phenological dataset, derived from over 600 site-years of PhenoCam imagery. For each archived image (ca. 5 million), we extracted RGB (red, green, blue) color channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 minute) imagery, we derived time series characterizing vegetation color, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with a single annual cycle of vegetation activity, we derived estimates, with uncertainties, for the start, middle, and end of spring and autumn phenological transitions.

Given the lack of multi-year, standardized, and geographically distributed phenological data for North America, we anticipate that these datasets will be widely used by researchers in a variety of fields. Shifts in phenology are a particularly tangible example of the biological impacts of climate change, and thus these data may also find use in science education and outreach to the general public.