Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset

• Published in: Scientific Data
• Main Authors: Seyednasrollah, Bijan, Young, Adam M., Hufkens, Koen, Milliman, Tom, Friedl, Mark A., Frolking, Steve, Richardson, Andrew D.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2019
• Subjects: Library and Information Sciences; Statistics, Probability and Uncertainty; Computer Science Applications; Education; Information Systems; Statistics and Probability; Tundra
• Online Access: http://dx.doi.org/10.1038/s41597-019-0229-9; http://www.nature.com/articles/s41597-019-0229-9.pdf; http://www.nature.com/articles/s41597-019-0229-9

Abstract Monitoring vegetation phenology is critical for quantifying climate change impacts on ecosystems. We present an extensive dataset of 1783 site-years of phenological data derived from PhenoCam network imagery from 393 digital cameras, situated from tropics to tundra across a wide range of plant functional types, biomes, and climates. Most cameras are located in North America. Every half hour, cameras upload images to the PhenoCam server. Images are displayed in near-real time and provisional data products, including timeseries of the Green Chromatic Coordinate (Gcc), are made publicly available through the project web page ( https://phenocam.sr.unh.edu/webcam/gallery/ ). Processing is conducted separately for each plant functional type in the camera field of view. The PhenoCam Dataset v2.0, described here, has been fully processed and curated, including outlier detection and expert inspection, to ensure high quality data. This dataset can be used to validate satellite data products, to evaluate predictions of land surface models, to interpret the seasonality of ecosystem-scale CO 2 and H 2 O flux data, and to study climate change impacts on the terrestrial biosphere.