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A global moderate resolution dataset of gross primary production of vegetation for 2000–2016

This dataset contains GPP from Vegetation Photosynthesis Model (VPM) at two spatial resolution (0.05 and 0.5 degree) and three temporal resolution (8-day, monthly, annual). The units for the three temporal resolution are g C m-2 day-1, g C m-2 month-1, g C m-2 year-1, with no conversion factor. The original 500 m 8-day GPP product covering 2000-2016 is also available upon request (yaozhang@ou.edu or xiangming.xiao@ou.edu).

This GPP dataset is based on an improved light use efficiency theory and is driven by satellite data from MODIS and climate data from NCEP Reanalysis II. It also employs a state-of-the-art vegetation index (VI) gap-filling and smoothing algorithm and a separate treatment for C3/C4 photosynthesis pathways. All these improvements aim to solve several critical problems existing in current GPP products. With a satisfactory performance when validated against in situ GPP estimates, this dataset offers an alternative GPP estimate for regional to global carbon cycle studies.

Dataset Info

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FieldValue
Authors
Zhang, Yao
(ORCID)
Xiao, Xiangming
(ORCID)
Wu, Xiaocui
Zhou, Sha
(ORCID)
Zhang, Geli
Qin, Yuanwei
Dong, Jinwei
Spatial / Geographical Coverage Location
Global
Temporal Coverage
2000/2016
Intended Use
This GPP dataset is based on an improved light use efficiency theory and is driven by satellite data from MODIS and climate data from NCEP Reanalysis II. It also employs a state-of-the-art vegetation index (VI) gap-filling and smoothing algorithm and a separate treatment for C3/C4 photosynthesis pathways. All these improvements aim to solve several critical problems existing in current GPP products. With a satisfactory performance when validated against in situ GPP estimates, this dataset offers an alternative GPP estimate for regional to global carbon cycle studies.
Use Limitations
The GPP for gridcells in coastal regions (in 0.05°×0.05° and 0.5°×0.5° spatial resolution products) are averaged over the entire gridcell but land only, therefore, the land area fraction is not needed when calculating the regional sum.
Publisher
Scientific Data
Contact Name
Xiao, Xiangming
Contact Email
Public Access Level
Public
Primary Article

Zhang, Y., Xiao, X., Wu, X., Zhou, S., Zhang, G., Qin, Y., & Dong, J. (2017). A global moderate resolution dataset of gross primary production of vegetation for 2000–2016. Scientific Data, 4, sdata2017165. https://doi.org/10.1038/sdata.2017.165

Related Article

Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., & Huang, X. (2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment, 114, 168–182.

Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.-K., Hnilo, J. J., Fiorino, M. & Potter, G. L. (2002). NCEP-DOE AMIP-II Reanalysis (R-2), Bull. Amer. Meteor. Soc., 83, 1631-1643.

Ramankutty, N., Evan, A. T., Monfreda, C., & Foley, J. A. (2008). Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles 22, GB1003, doi:10.1029/2007GB002952.

Cites Other Datasets
Related Content
License
Funding Source(s)
National Institute of Food and Agriculture
2013-69002-23146
National Institute of Food and Agriculture
2016-68002-24967
National Science Foundation
IIA-1301789
National Aeronautics and Space Administration
GeoCarb Contract # 80LARC17C0001
Dataset DOI (digital object identifier)
10.1038/sdata.2017.165
Program Code
005:037 - Department of Agriculture - Research and Education
Bureau Code
005:20 - National Institute of Food and Agriculture
Modified Date
2019-05-31
Release Date
2018-03-02
Ag Data Commons Keywords: 
  • Agroecosystems & Environment
  • Weather and Climate
  • Agroecosystems & Environment
  • Plants & Crops
  • Crop production
  • Plants & Crops
  • Maps & Multimedia