This data set is only available for a restricted user group, please contact us if you want to access these data.
The Fraction of green Vegetation Cover (FCOVER) corresponds to the fraction of ground covered by green vegetation. Practically, it quantifies the spatial extent of the vegetation. It is independent from the illumination direction and it is sensitive to the vegetation amount. FCOVER is derived from the Leaf Area Index (LAI) and a number of structural parameters of the canopy. Used are top-of-canopy directionally normalized reflectances from SPOT-4 and -5 VEGETATION sensor and - later - the PROBA-V in the red, near-infrared, and shortwave infrared bands. These are used in a neural network approach which is trained with the best estimate of FCOVER from MODIS and CYCLOPES.
For more information we refer to the ATBDs mentioned in the references section.
This is version 2 of this data set provided by COPERNICUS Global Land Service.
Data were downloaded in netCDF file format with 1/112° grid cell resolution and global coverage. This data are available from ICDC on request. For the main data set offered here, data were block-averaged onto a 0.5° x 0.5° plate carree grid. Data are available for the latitude range 60°S to 80°N. Note, however, that limited solar illumination reduces the maximum northern latitude to smaller values during winter.
Last update of data set at ICDC: August 30, 2019.
Period and temporal resolution:
Spatial coverage and resolution:
The original data set at 1/112° grid resolution contains a bit-wise to read quality flag. The content of the flag can be read under http://land.copernicus.eu/global/products/fcover under "Technical".
The 0.5° x 0.5° data set offered here contains two basic separate flags. One flag refers to the two surface types where FCOVER retrieval is either impossible or prone to larger uncertainties. The other flag refers to the type of retrieval, i.e. whether data are interpolated or whether special corrections were applied to account for high latitude / high solar zenith angle illumination conditions. In addition, only the valid 1/112° x 1/112° grid points are used to compute the average value of the FCOVER and its uncertainty. As can be seen in the parameters section we give number of land pixels, number of valid pixels, and number of usable satellite data to convey information about reliability. We recommend to read the text given in the netCDF files.
FCOVER products have been validated and are reported to have a good quality, showing a spatial consistent global distribution of retrievals. Temporal profiles are very smooth and are highly consistent from year to year. Comparison with ground data shows that target accuracy is achieved, and no bias was detected. This applies to FCOVER based on SPOT-4 and -5 as well as on PROBA-V. More information about the validation efforts can be found in the validation reports listed under references.
We would like to mention that for continuing the SPOT-4 and -5 time series with PROBA-V some pre-processing needs to be done. Information about this given in this report.
Upon using this data please cite as follows:
Baret, F., et al. (2013). GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production. Remote Sensing of Environment, 137: 299-309
Camacho, F., et al. (2013). GEOV1: LAI, FAPAR Essential Climate Variables and FCOVER global time series capitalizing over existing products. Part 2: Validation and intercomparison with reference products. Remote Sensing of Environment 137: 310-329
The product was generated by the land service of Copernicus, the Earth Observation programme of the European Commission. The research leading to the current version of the product has received funding from various European Commission Research and Technical Development programmes. The product is based on SPOT/VGT 1km data ((c) CNES / PROBA-V 1km data ((c) ESA and distributed by VITO), last access date: 05/08/2019, provided on 0.5 degree x 0.5 degree plate carree grid in NetCDF file format by the Integrated Climate Data Center (ICDC, icdc.cen.uni-hamburg.de) University of Hamburg, Hamburg, Germany.