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. Here we present a dataset, consisting of ~750 site-years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour 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 colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with a single annual cycle of vegetation activity, we provide date estimates, with uncertainties, for the start, middle, and end of spring green-up and autumn green-down (senescent) phases. The PhenoCam database and R toolbox can be used for phenological model validation and development, evaluation of satellite remote sensing data products, and studies of climate change impacts on terrestrial ecosystems.Install Data Locally     Explore Data Online
Richardson, A.D., Hufkens, K., Milliman, T., Aubrecht, D.M., Chen, M., Gray, J.M., Johnston, M.R., Keenan, T.F., Klosterman, S.T., Kosmala, M., Melaas, E.K., Friedl, M.A., Frolking, S. 2018. Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery. Scientific Data. 5: 180028
Hufkens K., Basler J. D., Milliman T. Melaas E., Richardson A.D. 2018. An integrated phenology modelling framework in R: Phenology modelling with phenor. Methods in Ecology & Evolution. 9:1-10.
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