Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset
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 funct...
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ftinraparis:oai:prodinra.inra.fr:488800 2023-05-15T18:40:26+02:00 Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset Seyednasrollah, Bijan Young, Adam M. Hufkens, Koen Milliman, Tom Friedl, Mark A. Frolking, Steve Richardson, Andrew D. 2019 application/pdf http://prodinra.inra.fr/ft/1D7B97D3-6E3B-448A-A92D-42EDD2334CB1 http://prodinra.inra.fr/record/488800 https://doi.org/10.1038/s41597-019-0229-9 eng eng https://creativecommons.org/licenses/by/3.0/ CC-BY Scientific Data 1 (6), 1-11. (2019) ARTICLE 2019 ftinraparis https://doi.org/10.1038/s41597-019-0229-9 2019-11-26T23:25:43Z 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 CO2 and H2O flux data, and to study climate change impacts on the terrestrial biosphere.[br/] Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.9913694 Article in Journal/Newspaper Tundra Institut National de la Recherche Agronomique: ProdINRA Scientific Data 6 1 |
institution |
Open Polar |
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Institut National de la Recherche Agronomique: ProdINRA |
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ftinraparis |
language |
English |
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 CO2 and H2O flux data, and to study climate change impacts on the terrestrial biosphere.[br/] Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.9913694 |
format |
Article in Journal/Newspaper |
author |
Seyednasrollah, Bijan Young, Adam M. Hufkens, Koen Milliman, Tom Friedl, Mark A. Frolking, Steve Richardson, Andrew D. |
spellingShingle |
Seyednasrollah, Bijan Young, Adam M. Hufkens, Koen Milliman, Tom Friedl, Mark A. Frolking, Steve Richardson, Andrew D. Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset |
author_facet |
Seyednasrollah, Bijan Young, Adam M. Hufkens, Koen Milliman, Tom Friedl, Mark A. Frolking, Steve Richardson, Andrew D. |
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 |
2019 |
url |
http://prodinra.inra.fr/ft/1D7B97D3-6E3B-448A-A92D-42EDD2334CB1 http://prodinra.inra.fr/record/488800 https://doi.org/10.1038/s41597-019-0229-9 |
genre |
Tundra |
genre_facet |
Tundra |
op_source |
Scientific Data 1 (6), 1-11. (2019) |
op_rights |
https://creativecommons.org/licenses/by/3.0/ |
op_rightsnorm |
CC-BY |
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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1766229792710983680 |