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

doi:10.1038/sdata.2018.28

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

Journal Article · Tue Mar 13 00:00:00 EDT 2018 · Scientific Data

DOI:https://doi.org/10.1038/sdata.2018.28· OSTI ID:1433125

Richardson, Andrew D. ^[1]; Hufkens, Koen ^[2]; Milliman, Tom ^[3]; Aubrecht, Donald M. ^[2]; Chen, Min ^[2]; Gray, Josh M. ^[4]; Johnston, Miriam R. ^[2]; Keenan, Trevor F. ^[5]; Klosterman, Stephen T. ^[2]; Kosmala, Margaret ^[2]; Melaas, Eli K. ^[6]; Friedl, Mark A. ^[6]; Frolking, Steve ^[3]

Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology; Northern Arizona Univ., Flagstaff, AZ (United States). School of Informatics, Computing and Cyber Systems; Northern Arizona Univ., Flagstaff, AZ (United States). Center for Ecosystem Science and Society
Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology
Univ. of New Hampshire, Durham, NH (United States). Earth Systems Research Center
Boston Univ., MA (United States). Dept. of Earth and Environment; North Carolina State Univ., Raleigh, NC (United States). Dept. of Forestry and Environmental Resources
Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Sciences
Boston Univ., MA (United States). Dept. of Earth and Environment

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. Lastly, 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.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231; AC05-76RL01830; SC0016011

OSTI ID:: 1433125

Alternate ID(s):: OSTI ID: 1773102

Report Number(s):: PNNL-SA--133983; ark:/13030/qt46v7n34w

Journal Information:: Scientific Data, Journal Name: Scientific Data Vol. 5; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cryptic phenology in plants: Case studies, implications, and recommendations Albert, Loren P.; Restrepo‐Coupe, Natalia; Smith, Marielle N. Global Change Biology, Vol. 25, Issue 11 https://doi.org/10.1111/gcb.14759	journal	August 2019
Characteristics of free air carbon dioxide enrichment of a northern temperate mature forest Hart, Kris M.; Curioni, Giulio; Blaen, Phillip Global Change Biology, Vol. 26, Issue 2 https://doi.org/10.1111/gcb.14786	journal	September 2019
Refining the role of phenology in regulating gross ecosystem productivity across European peatlands Koebsch, Franziska; Sonnentag, Oliver; Järveoja, Järvi Global Change Biology https://doi.org/10.1111/gcb.14905	journal	December 2019
Tracking seasonal rhythms of plants in diverse ecosystems with digital camera imagery Richardson, Andrew D. New Phytologist, Vol. 222, Issue 4 https://doi.org/10.1111/nph.15591	journal	December 2018
Growth and opportunities in networked synthesis through AmeriFlux Keenan, Trevor F.; Moore, David J. P.; Desai, Ankur New Phytologist, Vol. 222, Issue 4 https://doi.org/10.1111/nph.15835	journal	May 2019
Detecting the onset of autumn leaf senescence in deciduous forest trees of the temperate zone Mariën, Bertold; Balzarolo, Manuela; Dox, Inge New Phytologist, Vol. 224, Issue 1 https://doi.org/10.1111/nph.15991	journal	June 2019
Effects of climate change on alpine plants and their pollinators Inouye, David W. Annals of the New York Academy of Sciences, Vol. 1469, Issue 1 https://doi.org/10.1111/nyas.14104	journal	April 2019
Comparison of Phenology Estimated from Reflectance-Based Indices and Solar-Induced Chlorophyll Fluorescence (SIF) Observations in a Temperate Forest Using GPP-Based Phenology as the Standard Lu, Xiaoliang; Liu, Zhunqiao; Zhou, Yuyu Remote Sensing, Vol. 10, Issue 6 https://doi.org/10.3390/rs10060932	journal	June 2018
Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem Melendo-Vega, José; Martín, M.; Pacheco-Labrador, Javier Remote Sensing, Vol. 10, Issue 12 https://doi.org/10.3390/rs10122061	journal	December 2018
A Comparison of the Signal from Diverse Optical Sensors for Monitoring Alpine Grassland Dynamics Rossi, Mattia; Niedrist, Georg; Asam, Sarah Remote Sensing, Vol. 11, Issue 3 https://doi.org/10.3390/rs11030296	journal	February 2019
Measuring Vegetation Phenology with Near-Surface Remote Sensing in a Temperate Deciduous Forest: Effects of Sensor Type and Deployment Liu, Fan; Wang, Xingchang; Wang, Chuankuan Remote Sensing, Vol. 11, Issue 9 https://doi.org/10.3390/rs11091063	journal	May 2019
Coupled Spatiotemporal Characterization of Monsoon Cloud Cover and Vegetation Phenology Sousa, Daniel; Small, Christopher; Spalton, Andrew Remote Sensing, Vol. 11, Issue 10 https://doi.org/10.3390/rs11101203	journal	May 2019
The Use of UAV Mounted Sensors for Precise Detection of Bark Beetle Infestation Klouček, Tomáš; Komárek, Jan; Surový, Peter Remote Sensing, Vol. 11, Issue 13 https://doi.org/10.3390/rs11131561	journal	July 2019
Influence of Landscape Heterogeneity and Spatial Resolution in Multi-Temporal In Situ and MODIS NDVI Data Proxies for Seasonal GPP Dynamics Balzarolo, Manuela; Peñuelas, Josep; Veroustraete, Frank Remote Sensing, Vol. 11, Issue 14 https://doi.org/10.3390/rs11141656	journal	July 2019
Asymmetric Behavior of Vegetation Seasonal Growth and the Climatic Cause: Evidence from Long-Term NDVI Dataset in Northeast China Zhou, Yuke Remote Sensing, Vol. 11, Issue 18 https://doi.org/10.3390/rs11182107	journal	September 2019
Leafing Patterns and Drivers across Seasonally Dry Tropical Communities Alberton, Bruna; da Silva Torres, Ricardo; Sanna Freire Silva, Thiago Remote Sensing, Vol. 11, Issue 19 https://doi.org/10.3390/rs11192267	journal	September 2019
N : P stoichiometry and habitat effects on Mediterranean savanna seasonal root dynamics Nair, Richard K. F.; Morris, Kendalynn A.; Hertel, Martin Biogeosciences, Vol. 16, Issue 9 https://doi.org/10.5194/bg-16-1883-2019	journal	January 2019
A dataset of 30 m annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States Li, Xuecao; Zhou, Yuyu; Meng, Lin Earth System Science Data, Vol. 11, Issue 2 https://doi.org/10.5194/essd-11-881-2019	journal	January 2019
Comparison Of Large-Scale Citizen Science Data And Long-Term Study Data For Phenology Modeling Taylor, Shawn D.; Meiners, Joan M.; Riemer, Kristina Zenodo https://doi.org/10.5281/zenodo.1256705	text	January 2018
Coupled Spatiotemporal Characterization of Monsoon Cloud Cover and Vegetation Phenology Sousa, Daniel John; Small, Christopher; Spalton, Andrew Columbia University https://doi.org/10.7916/d8-p5zf-ws16	text	January 2019

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