Articles | Volume 13, issue 3
https://doi.org/10.5194/bg-13-625-2016
https://doi.org/10.5194/bg-13-625-2016
Research article
 | 
03 Feb 2016
Research article |  | 03 Feb 2016

Global assessment of Vegetation Index and Phenology Lab (VIP) and Global Inventory Modeling and Mapping Studies (GIMMS) version 3 products

M. Marshall, E. Okuto, Y. Kang, E. Opiyo, and M. Ahmed

Related authors

DYNAMIC TIME WARPING FOR CROPS MAPPING
M. Belgiu, Y. Zhou, M. Marshall, and A. Stein
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 947–951, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-947-2020,https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-947-2020, 2020
Continuous and consistent land use/cover change estimates using socio-ecological data
Michael Marshall, Michael Norton-Griffiths, Harvey Herr, Richard Lamprey, Justin Sheffield, Tor Vagen, and Joseph Okotto-Okotto
Earth Syst. Dynam., 8, 55–73, https://doi.org/10.5194/esd-8-55-2017,https://doi.org/10.5194/esd-8-55-2017, 2017
Short summary

Related subject area

Earth System Science/Response to Global Change: Evolution of System Earth
Technical note: Low meteorological influence found in 2019 Amazonia fires
Douglas I. Kelley, Chantelle Burton, Chris Huntingford, Megan A. J. Brown, Rhys Whitley, and Ning Dong
Biogeosciences, 18, 787–804, https://doi.org/10.5194/bg-18-787-2021,https://doi.org/10.5194/bg-18-787-2021, 2021
Short summary
Understanding tropical forest abiotic response to hurricanes using experimental manipulations, field observations, and satellite data
Ashley E. Van Beusekom, Grizelle González, Sarah Stankavich, Jess K. Zimmerman, and Alonso Ramírez
Biogeosciences, 17, 3149–3163, https://doi.org/10.5194/bg-17-3149-2020,https://doi.org/10.5194/bg-17-3149-2020, 2020
Short summary
Towards a global understanding of vegetation–climate dynamics at multiple timescales
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020,https://doi.org/10.5194/bg-17-945-2020, 2020
Short summary
Evaluating and improving the Community Land Model's sensitivity to land cover
Ronny Meier, Edouard L. Davin, Quentin Lejeune, Mathias Hauser, Yan Li, Brecht Martens, Natalie M. Schultz, Shannon Sterling, and Wim Thiery
Biogeosciences, 15, 4731–4757, https://doi.org/10.5194/bg-15-4731-2018,https://doi.org/10.5194/bg-15-4731-2018, 2018
Short summary
The extant shore platform stromatolite (SPS) facies association: a glimpse into the Archean?
Alan Smith, Andrew Cooper, Saumitra Misra, Vishal Bharuth, Lisa Guastella, and Riaan Botes
Biogeosciences, 15, 2189–2203, https://doi.org/10.5194/bg-15-2189-2018,https://doi.org/10.5194/bg-15-2189-2018, 2018
Short summary

Cited articles

Asrar, G., Myneni, R. B., and Choudhury, B. J.: Spatial heterogeneity in vegetation canopies and remote sensing of absorbed photosynthetically active radiation: A modeling study, Remote Sens. Environ., 41, 85–103, 1992.
Barichivich, J., Briffa, K. R., Myneni, R. B., Osborn, T. J., Melvin, T. M., Ciais, P., Piao, S., and Tucker, C.: Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011, Glob. Change Biol., 19, 3167–3183, 2013.
Beck, H. E., McVicar, T. R., van Dijk, A. I. J. M., Schellekens, J., de Jeu, R. A. M., and Bruijnzeel, L. A.: Global evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery, Remote Sens. Environ., 115, 2547–2563, 2011.
Beer, A.: Bestimmung der Absorption des rothen Lichts in farbigen Flüssigkeiten, Ann. Phys. U. Chem., 1852.
Download
Short summary
We compared two new Earth observation based long-term global vegetation index products used in global change research (Global Inventory Modeling and Mapping Studies and Vegetation Index and Phenology Lab- VIP version 3). The two products showed a high level of consistency throughout the primary growing season and were less consistent during green-up and brown-down that impacted trends in phenology. VIP was generally higher and more variable leading to poorer correlations with in situ data
Altmetrics
Final-revised paper
Preprint