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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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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. |
format | Online Article Text |
id | pubmed-5848786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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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