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spelling ftosti:oai:osti.gov:1802809 2023-07-30T04:07:20+02:00 Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset Seyednasrollah, Bijan Young, Adam M. Hufkens, Koen Ghent Univ., Ghent . Faculty of Bioscience Engineering; National Centre for Scientific Research-Mixed Organizations , Paris Milliman, Tom Univ. of New Hampshire, Durham, NH . Earth Systems Research Center Friedl, Mark A. Boston Univ., MA . Dept. of Earth and Environment Frolking, Steve Univ. of New Hampshire, Durham, NH . Earth Systems Research Center Richardson, Andrew D. Northern Arizona Univ., Flagstaff, AZ . School of Informatics, Computing, and Cyber Systems Northern Arizona Univ., Flagstaff, AZ . Center for Ecosystem Science and Society 2023-07-04 application/pdf http://www.osti.gov/servlets/purl/1802809 https://www.osti.gov/biblio/1802809 https://doi.org/10.1038/s41597-019-0229-9 unknown http://www.osti.gov/servlets/purl/1802809 https://www.osti.gov/biblio/1802809 https://doi.org/10.1038/s41597-019-0229-9 doi:10.1038/s41597-019-0229-9 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.1038/s41597-019-0229-9 2023-07-11T10:04:50Z 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. Other/Unknown Material Tundra SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Scientific Data 6 1
institution Open Polar
collection SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
op_collection_id ftosti
language unknown
topic 54 ENVIRONMENTAL SCIENCES
spellingShingle 54 ENVIRONMENTAL SCIENCES
Seyednasrollah, Bijan
Young, Adam M.
Hufkens, Koen Ghent Univ., Ghent . Faculty of Bioscience Engineering; National Centre for Scientific Research-Mixed Organizations , Paris
Milliman, Tom Univ. of New Hampshire, Durham, NH . Earth Systems Research Center
Friedl, Mark A. Boston Univ., MA . Dept. of Earth and Environment
Frolking, Steve Univ. of New Hampshire, Durham, NH . Earth Systems Research Center
Richardson, Andrew D. Northern Arizona Univ., Flagstaff, AZ . School of Informatics, Computing, and Cyber Systems
Northern Arizona Univ., Flagstaff, AZ . Center for Ecosystem Science and Society
Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
topic_facet 54 ENVIRONMENTAL SCIENCES
description 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.
author Seyednasrollah, Bijan
Young, Adam M.
Hufkens, Koen Ghent Univ., Ghent . Faculty of Bioscience Engineering; National Centre for Scientific Research-Mixed Organizations , Paris
Milliman, Tom Univ. of New Hampshire, Durham, NH . Earth Systems Research Center
Friedl, Mark A. Boston Univ., MA . Dept. of Earth and Environment
Frolking, Steve Univ. of New Hampshire, Durham, NH . Earth Systems Research Center
Richardson, Andrew D. Northern Arizona Univ., Flagstaff, AZ . School of Informatics, Computing, and Cyber Systems
Northern Arizona Univ., Flagstaff, AZ . Center for Ecosystem Science and Society
author_facet Seyednasrollah, Bijan
Young, Adam M.
Hufkens, Koen Ghent Univ., Ghent . Faculty of Bioscience Engineering; National Centre for Scientific Research-Mixed Organizations , Paris
Milliman, Tom Univ. of New Hampshire, Durham, NH . Earth Systems Research Center
Friedl, Mark A. Boston Univ., MA . Dept. of Earth and Environment
Frolking, Steve Univ. of New Hampshire, Durham, NH . Earth Systems Research Center
Richardson, Andrew D. Northern Arizona Univ., Flagstaff, AZ . School of Informatics, Computing, and Cyber Systems
Northern Arizona Univ., Flagstaff, AZ . Center for Ecosystem Science and Society
author_sort Seyednasrollah, Bijan
title Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
title_short Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
title_full Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
title_fullStr Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
title_full_unstemmed Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
title_sort tracking vegetation phenology across diverse biomes using version 2.0 of the phenocam dataset
publishDate 2023
url http://www.osti.gov/servlets/purl/1802809
https://www.osti.gov/biblio/1802809
https://doi.org/10.1038/s41597-019-0229-9
genre Tundra
genre_facet Tundra
op_relation http://www.osti.gov/servlets/purl/1802809
https://www.osti.gov/biblio/1802809
https://doi.org/10.1038/s41597-019-0229-9
doi:10.1038/s41597-019-0229-9
op_doi https://doi.org/10.1038/s41597-019-0229-9
container_title Scientific Data
container_volume 6
container_issue 1
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