Published August 24, 2020 | Version 1.0
Dataset Open

Global vegetation productivity from 1981 to 2018 estimated from remote sensing data

  • 1. Faculty of Geographical Sciences, Beijing Normal University
  • 1. ROR icon Beijing Normal University

Description

The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/).

The  MUSES global vegetation productivity dataset includes gross primary productivity (GPP) and net primary productivity (NPP) data from 1981 to 2018. GPP and NPP were estimated with a light use efficiency (LUE) model and  MUSES leaf and index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) products. The detail information of the products is as below:

Name: MUSES 5-km global GPP and NPP products

Period: 1981-2018

Spatial resolution: 0.05°

Temporal resolution: 8 days

Projection: geographic latitude/longitude

Data format: Tiff

Data type: integer (16bit)

Upper left coordinates: -180°E, 90°N

Scale factor: 100

Unit: gCm-2d-1

 

Notes

This dataset was supported by the National Key R&D Program of China (2017YFA0603002, 2016YFB0501502).

Files

Algorithm of global gross and net primary productivity products.pdf

Files (18.4 GB)

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Additional details

References

  • Wang, J.M., Sun, R., Zhang, H.L., Xiao, Z.Q., Zhu A.R., Wang, M.J., Yu, T., Xiang, K.L., New global MuSyQ GPP/NPP remote sensing products from 1981 to 2018. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14, 5596-5612.
  • Wang, M.J.; Sun, R.; Zhu, A.R.; Xiao, Z. Q. Evaluation and Comparison of Light Use Efficiency and Gross Primary Productivity Using Three Different Approaches. Remote Sensing. 2020, 12, 1003.