Accès ouvert déclaré
2017
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PhenoCam Dataset v1.0: Vegetation Phenology from Digital Camera Imagery, 2000-2015
A D Richardson, Koen Hufkens, Tom Milliman, Donald M. Aubrecht, Ming Chen, Josh Gray, Miriam R. Johnston, Trevor F. Keenan, Stephen Klosterman, Margaret Kosmala, E. K. Melaas, FRIEDL ‡, Steve Frolking, Michael Abraha, Merryl Alber, M. E. Apple, B. E. Law, T. Andrew Black, Peter D. Blanken, Dawn M. Browning, Syndonia Bret-Harte, N. A. Brunsell, S.P. Burns, Edoardo Cremonese, A.R. Desai, A.L. Dunn, David M. Eissenstat, S.E. Euskirchen, Lawrence B. Flanagan, Brandon Forsythe, Julia Gallagher, Lingjia Gu, D. Y. Hollinger, John W. Jones, Jason King, Ola Langvall, J. H. McCaughey, Patrick McHale, G.A. Meyer, M.J. Mitchell, M. Migliavacca, Zoran Nesic, Asko Noormets, Kimberly A. Novick, Jerome O’Connell, Ayame Oishi, W. Wyatt Oswald, Timothy D. Perkins, Russell Phillips, Schwartz, Russell L. Scott, Oliver Sonnentag, Jonathan E. Thom, Dennis Baldocchi, Joseph Verfaillie
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Le résumé fourni par la source
This data set provides a time series of vegetation phenological observations for 133 sites across diverse ecosystems of North America and Europe from 2000-2015. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals.
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Les sujets associés
Remote Sensing in AgricultureSpecies Distribution and Climate ChangeRemote Sensing and LiDAR Applications