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Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characte...

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Autores principales: Richardson, Andrew D., Hufkens, Koen, Milliman, Tom, Aubrecht, Donald M., Chen, Min, Gray, Josh M., Johnston, Miriam R., Keenan, Trevor F., Klosterman, Stephen T., Kosmala, Margaret, Melaas, Eli K., Friedl, Mark A., Frolking, Steve
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5848786/
https://www.ncbi.nlm.nih.gov/pubmed/29533393
http://dx.doi.org/10.1038/sdata.2018.28
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author Richardson, Andrew D.
Hufkens, Koen
Milliman, Tom
Aubrecht, Donald M.
Chen, Min
Gray, Josh M.
Johnston, Miriam R.
Keenan, Trevor F.
Klosterman, Stephen T.
Kosmala, Margaret
Melaas, Eli K.
Friedl, Mark A.
Frolking, Steve
author_facet Richardson, Andrew D.
Hufkens, Koen
Milliman, Tom
Aubrecht, Donald M.
Chen, Min
Gray, Josh M.
Johnston, Miriam R.
Keenan, Trevor F.
Klosterman, Stephen T.
Kosmala, Margaret
Melaas, Eli K.
Friedl, Mark A.
Frolking, Steve
author_sort Richardson, Andrew D.
collection PubMed
description Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated 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 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.
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spelling pubmed-58487862018-03-24 Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery Richardson, Andrew D. Hufkens, Koen Milliman, Tom Aubrecht, Donald M. Chen, Min Gray, Josh M. Johnston, Miriam R. Keenan, Trevor F. Klosterman, Stephen T. Kosmala, Margaret Melaas, Eli K. Friedl, Mark A. Frolking, Steve Sci Data Data Descriptor Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated 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 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems. Nature Publishing Group 2018-03-13 /pmc/articles/PMC5848786/ /pubmed/29533393 http://dx.doi.org/10.1038/sdata.2018.28 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Richardson, Andrew D.
Hufkens, Koen
Milliman, Tom
Aubrecht, Donald M.
Chen, Min
Gray, Josh M.
Johnston, Miriam R.
Keenan, Trevor F.
Klosterman, Stephen T.
Kosmala, Margaret
Melaas, Eli K.
Friedl, Mark A.
Frolking, Steve
Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
title Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
title_full Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
title_fullStr Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
title_full_unstemmed Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
title_short Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
title_sort tracking vegetation phenology across diverse north american biomes using phenocam imagery
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5848786/
https://www.ncbi.nlm.nih.gov/pubmed/29533393
http://dx.doi.org/10.1038/sdata.2018.28
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