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

dataset
posted on 2024-02-08, 21:22 authored by Yao Zhang, Xiangming Xiao, Xiaocui Wu, Sha Zhou, Geli Zhang, Yuanwei Qin, Jinwei Dong

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.


Resources in this dataset:

Resource Title: A global moderate resolution dataset of gross primary production of vegetation for 2000–2016..

File Name: Web Page, url: https://doi.org/10.1038/sdata.2017.165

Data links included in the paper, as well as in Related Content section of this metadata record.

Gross Primary Production (GPP) from Vegetation Photosynthesis Model (VPM) at 0.05 and 0.5 degree with 8-day, monthly, and annual resolution 


Raw 500 m 8-day GPP product with the data quality layer

Funding

USDA-NIFA: 2013-69002-23146

USDA-NIFA: 2016-68002-24967

National Science Foundation: IIA-1301789

National Aeronautics and Space Administration: GeoCarb Contract # 80LARC17C0001

History

Data contact name

Xiao, Xiangming

Data contact email

xiangming.xiao@ou.edu

Publisher

Scientific Data

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.

Temporal Extent Start Date

2000-01-01

Temporal Extent End Date

2016-12-31

Theme

  • Not specified

Geographic location - description

Global

ISO Topic Category

  • climatologyMeteorologyAtmosphere
  • environment
  • geoscientificInformation
  • imageryBaseMapsEarthCover

National Agricultural Library Thesaurus terms

data collection; vegetation; photosynthesis; models; remote sensing; moderate resolution imaging spectroradiometer; meteorological data; vegetation index; algorithms; C3 photosynthesis; C4 photosynthesis; primary productivity; prediction; climate change; eddy covariance; temperature; ecology; carbon cycle; Biological Sciences; Natural Resources Earth and Environmental Sciences

Pending citation

  • No

Public Access Level

  • Public

Preferred dataset citation

Zhang, Yao; Xiao, Xiangming; Wu, Xiaocui; Zhou, Sha; Zhang, Geli; Qin, Yuanwei; Dong, Jinwei (2018). A global moderate resolution dataset of gross primary production of vegetation for 2000–2016. Scientific Data. https://doi.org/10.1038/sdata.2017.165

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