MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 250m SIN Grid in 2007 (185–361)
View DatasetDescription
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/). This dataset is the MUSES global FVC product at 250m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 250m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao et al., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2007 (185–361). Please click here to download the MUSES FVC product in 2007 (001–177) and click here to download the MUSES FVC product in 2008 (001–177). Dataset Characteristics: Spatial Coverage: Global Temporal Coverage: 2007 (185–361) Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 100 Citation (Please cite this paper whenever these data are used): Xiao Zhiqiang, et al. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. Remote Sensing, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao ([email protected]).
Citations (0)
No citations found
Mentions (0)
No mentions found
Metrics Over Time
Publication Details
DOI
Publisher
Zenodo
Subfield
Computer Graphics and Computer-Aided Design
Field
Computer Science
Domain
Physical Sciences
Confidence Score
31%
Source
Scholar Data Model