Dataset
ESA Vegetation Parameters Climate Change Initiative (VP_cci): LAI and fAPAR, Version 2.0
Abstract
This dataset comprises the Climate Research Data Package 2 from the ESA Climate Change Initiative Vegetation Parameters Project (VP_cci). It is a multi-sensor, jointly retrieved dataset of effective Leaf Area Index (LAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR), gridded at 1 km resolution for the period 2000-2020. The dataset is based on data from the satellite instruments SPOT4/5-VEGETATION1/2, PROBA-V, Metop/A/C-AVHRR, SNPP-VIIRS and Sentinel-3A/B-OLCI as input data.
LAI (effective) and fAPAR are retrieved using OptiSAIL (see Blessing and Giering, 2021 doi:10.20944/preprints202109.0147.v1). The dataset is processed for a north-south transect from Finland to South-Africa and the full Mediterranean area, as well as for a set of globally distributed sites that is representative for all biomes and for those sites where in-situ reference data is available.
The temporal resolution of both datasets is 5 days, but is computed using data selected from a symmetric 10-day window. The data are not smoothed in time. The transect is ordered in tiles (see the linked Product User Guide for reference). These files contain the fully validated layers of (effective) LAI, fAPAR, their uncertainties and the correlation between both. The sites additionally include the variables Chlorophyll a+b leaf pigment concentration (Cab), the fraction of Chlorophyll Absorbed Photosynthetically Active Radiation (fAPAR_Cab) and Surface Albedo calculated as bi-hemispheric reflectance (BHR) for diffuse illumination with a reference spectrum for spectral broadband intervals at visible wavelengths (VIS, 400-700 nm), near-infrared wavelengths (NIR, 700-2500 nm), and for the combined shortwave range (SW, 400-2500 nm), as well as directional-hemispherical reflectance (DHR) for the same spectral broadbands, computed for local solar noon. These additional variables are not validated.
Compared to the previous dataset (CRDP-1), CRDP-2 has a better completeness, smoother temporal profiles and higher accuracy, especially for fAPAR. Further details about the data, including validation and intercomparison with similar datasets, can be found in the associated PDF documentation.
Tools are available for using the datasets from https://github.com/Christiaanvandertol/VegetationCCI. Three notebooks are available
- esacci.ipynb: A Jupyter Notebook to access, download and plot the data of a single tile, and to carry out a spatial aggregation
- esacci_multi.ipynb: A Jupyter Notebook to access, download and plot time series for a specific location from tiles
- ESACCI_LAI_clumping_correction.ipynb: A Jupyter Notebook to add the clumping index correction from MODIS and to calculate true LAI.
Details
| Previous Info: |
No news update for this record
|
|---|---|
| Previously used record identifiers: |
No related previous identifiers.
|
| Access rules: |
Please contact the data centre for details on how to access these data.
Use of these data is covered by the following licence(s): https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_vegetation_parameters_terms_and_conditions.pdf When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data was produced by the ESA Vegetation Parameters CCI team as part of the ESA Climate Change Initiative (CCI) and is being held on the CEDA (Centre for Environmental Data Analysis) archive as part of the ESA CCI Open Data Portal project. |
| Data Quality: |
See the Vegetation Parameters CCI documentation for information on data quality.
|
| File Format: |
Data are in NetCDF format
|
Related Documents
Process overview
Instrument/Platform pairings
| VEGETATION-1 | Deployed on: SPOT-4 |
| VEGETATION-2 | Deployed on: SPOT-5 |
| Végétation-P | Deployed on: PROBA-V |
| Advanced Very High Resolution Radiometer 3 (AVHRR/3) | Deployed on: Metop-A |
| Advanced Very High Resolution Radiometer 3 (AVHRR/3) | Deployed on: Metop-C |
| Suomi NPP: Visible Infrared Imaging Radiometer Suite (VIIRS) | Deployed on: SNPP |
| Sentinel 3 Ocean and Land Colour Instrument (OLCI) | Deployed on: Sentinel 3A |
| Sentinel 3 Ocean and Land Colour Instrument (OLCI) | Deployed on: Sentinel 3B |
Computation Element: 1
| Title | OptiSAIL retrieval |
| Abstract | The retrieval model OptiSAIL is built around the established components 4SAILH (Scattering of Arbitrarily Inclined Leaves, with 4-stream extension and hot-spot), PROSPECT-D (simulation of leaf spectra, version D including senescence; Féret et al., 2017), TARTES (Two-streAm Radiative Transfer in Snow; Libois et al., 2013), with the addition of an empirical soil reflectance model, a semi-empirical soil moisture model (Philpot, 2010), the Ross-Thick-Li-Sparse BRDF model, and a cloud contamination simulation. |
| Input Description | None |
| Output Description | None |
| Software Reference | Blessing, S., Giering, R. (2021). Simultaneous Retrieval of Soil, Leaf, and Canopy Parameters from Sentinel-3 OLCI and SLSTR Multi-spectral Top-of-Canopy Reflectances. Preprints. None |
| Output Description | None |
- units: 1
- var_id: BHR_NIR_BHR_SW_correl
- long_name: BHR_NIR BHR_SW standard_error_correlation
- units: 1
- var_id: BHR_NIR_DHR_NIR_correl
- long_name: BHR_NIR DHR_NIR standard_error_correlation
- units: 1
- var_id: BHR_NIR_DHR_SW_correl
- long_name: BHR_NIR DHR_SW standard_error_correlation
- units: 1
- var_id: BHR_NIR_DHR_VIS_correl
- long_name: BHR_NIR DHR_VIS standard_error_correlation
- units: 1
- var_id: BHR_NIR_ERR
- long_name: BHR_NIR standard_error
- units: 1
- var_id: BHR_SW_DHR_NIR_correl
- long_name: BHR_SW DHR_NIR standard_error_correlation
- units: 1
- var_id: BHR_SW_DHR_SW_correl
- long_name: BHR_SW DHR_SW standard_error_correlation
- units: 1
- var_id: BHR_SW_DHR_VIS_correl
- long_name: BHR_SW DHR_VIS standard_error_correlation
- units: 1
- var_id: BHR_SW_ERR
- long_name: BHR_SW standard_error
- units: 1
- var_id: BHR_VIS_BHR_NIR_correl
- long_name: BHR_VIS BHR_NIR standard_error_correlation
- units: 1
- var_id: BHR_VIS_BHR_SW_correl
- long_name: BHR_VIS BHR_SW standard_error_correlation
- units: 1
- var_id: BHR_VIS_DHR_NIR_correl
- long_name: BHR_VIS DHR_NIR standard_error_correlation
- units: 1
- var_id: BHR_VIS_DHR_SW_correl
- long_name: BHR_VIS DHR_SW standard_error_correlation
- units: 1
- var_id: BHR_VIS_DHR_VIS_correl
- long_name: BHR_VIS DHR_VIS standard_error_correlation
- units: 1
- var_id: BHR_VIS_ERR
- long_name: BHR_VIS standard_error
- units: 1
- var_id: Cab_BHR_NIR_correl
- long_name: Cab BHR_NIR standard_error_correlation
- units: 1
- var_id: Cab_BHR_SW_correl
- long_name: Cab BHR_SW standard_error_correlation
- units: 1
- var_id: Cab_BHR_VIS_correl
- long_name: Cab BHR_VIS standard_error_correlation
- units: 1
- var_id: Cab_DHR_NIR_correl
- long_name: Cab DHR_NIR standard_error_correlation
- units: 1
- var_id: Cab_DHR_SW_correl
- long_name: Cab DHR_SW standard_error_correlation
- units: 1
- var_id: Cab_DHR_VIS_correl
- long_name: Cab DHR_VIS standard_error_correlation
- units: 1
- var_id: Cab_LAI_correl
- long_name: Cab LAI standard_error_correlation
- units: 1
- var_id: Cab_fAPAR_correl
- long_name: Cab fAPAR standard_error_correlation
- units: 1
- var_id: Cab_fAPAR_Cab_correl
- long_name: Cab fAPAR_Cab standard_error_correlation
- var_id: Cab_ERR
- long_name: Cab standard_error
- units: ug.cm-2
- units: 1
- var_id: DHR_NIR_DHR_SW_correl
- long_name: DHR_NIR DHR_SW standard_error_correlation
- units: 1
- var_id: DHR_NIR_ERR
- long_name: DHR_NIR standard_error
- units: 1
- var_id: DHR_SW_ERR
- long_name: DHR_SW standard_error
- units: 1
- var_id: DHR_VIS_DHR_NIR_correl
- long_name: DHR_VIS DHR_NIR standard_error_correlation
- units: 1
- var_id: DHR_VIS_DHR_SW_correl
- long_name: DHR_VIS DHR_SW standard_error_correlation
- units: 1
- var_id: DHR_VIS_ERR
- long_name: DHR_VIS standard_error
- units: 1
- var_id: fAPAR_Cab
- long_name: DIAG fAPAR absorbed by Chlorophyll a+b
- units: 1
- var_id: fAPAR
- long_name: DIAG fraction of Absorbed Photosynthetically Active Radiation using diffuse ASTMG173
- units: 1
- var_id: LAI_BHR_NIR_correl
- long_name: LAI BHR_NIR standard_error_correlation
- units: 1
- var_id: LAI_BHR_SW_correl
- long_name: LAI BHR_SW standard_error_correlation
- units: 1
- var_id: LAI_BHR_VIS_correl
- long_name: LAI BHR_VIS standard_error_correlation
- units: 1
- var_id: LAI_DHR_NIR_correl
- long_name: LAI DHR_NIR standard_error_correlation
- units: 1
- var_id: LAI_DHR_SW_correl
- long_name: LAI DHR_SW standard_error_correlation
- units: 1
- var_id: LAI_DHR_VIS_correl
- long_name: LAI DHR_VIS standard_error_correlation
- units: 1
- var_id: LAI_fAPAR_correl
- long_name: LAI fAPAR standard_error_correlation
- units: 1
- var_id: LAI_fAPAR_Cab_correl
- long_name: LAI fAPAR_Cab standard_error_correlation
- units: m2.m-2
- var_id: LAI_ERR
- long_name: LAI standard_error
- units: 1
- var_id: n_bands_used
- long_name: Number of data contributions to cost function in retrival
- units: ug.cm-2
- var_id: Cab
- long_name: PROSPECT-D leaf chlorophyll a+b content
- units: 1
- var_id: p_chisquare
- long_name: Probability of Chi-square statistics; low values mark bad correspondence of model and data.
- var_id: LAI
- long_name: SAIL effective Leaf Area Index
- units: m2.m-2
- units: 1
- var_id: BHR_NIR
- long_name: bi-hemispherical reflectance (albedo) in the near infra-red range
- units: 1
- var_id: BHR_SW
- long_name: bi-hemispherical reflectance (albedo) in the shortwave range
- units: 1
- var_id: BHR_VIS
- long_name: bi-hemispherical reflectance (albedo) in the visible range
- var_id: crs
- units: 1
- var_id: DHR_NIR
- long_name: directional-hemispherical reflectance (black-sky albedo), NIR, at local solar noon
- units: 1
- var_id: DHR_SW
- long_name: directional-hemispherical reflectance (black-sky albedo), SW, at local solar noon
- units: 1
- var_id: DHR_VIS
- long_name: directional-hemispherical reflectance (black-sky albedo), VIS, at local solar noon
- units: 1
- var_id: fAPAR_BHR_NIR_correl
- long_name: fAPAR BHR_NIR standard_error_correlation
- units: 1
- var_id: fAPAR_BHR_SW_correl
- long_name: fAPAR BHR_SW standard_error_correlation
- units: 1
- var_id: fAPAR_BHR_VIS_correl
- long_name: fAPAR BHR_VIS standard_error_correlation
- units: 1
- var_id: fAPAR_DHR_NIR_correl
- long_name: fAPAR DHR_NIR standard_error_correlation
- units: 1
- var_id: fAPAR_DHR_SW_correl
- long_name: fAPAR DHR_SW standard_error_correlation
- units: 1
- var_id: fAPAR_DHR_VIS_correl
- long_name: fAPAR DHR_VIS standard_error_correlation
- units: 1
- var_id: fAPAR_fAPAR_Cab_correl
- long_name: fAPAR fAPAR_Cab standard_error_correlation
- units: 1
- var_id: fAPAR_ERR
- long_name: fAPAR standard_error
- units: 1
- var_id: fAPAR_Cab_BHR_NIR_correl
- long_name: fAPAR_Cab BHR_NIR standard_error_correlation
- units: 1
- var_id: fAPAR_Cab_BHR_SW_correl
- long_name: fAPAR_Cab BHR_SW standard_error_correlation
- units: 1
- var_id: fAPAR_Cab_BHR_VIS_correl
- long_name: fAPAR_Cab BHR_VIS standard_error_correlation
- units: 1
- var_id: fAPAR_Cab_DHR_NIR_correl
- long_name: fAPAR_Cab DHR_NIR standard_error_correlation
- units: 1
- var_id: fAPAR_Cab_DHR_SW_correl
- long_name: fAPAR_Cab DHR_SW standard_error_correlation
- units: 1
- var_id: fAPAR_Cab_DHR_VIS_correl
- long_name: fAPAR_Cab DHR_VIS standard_error_correlation
- units: 1
- var_id: fAPAR_Cab_ERR
- long_name: fAPAR_Cab standard_error
- var_id: invcode
- long_name: inversion code
- var_id: lat_bnds
- var_id: lon_bnds
- var_id: time_bnds
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- var_id: lat
- units: degrees_east
- standard_name: longitude
- var_id: lon
- standard_name: time
- var_id: time
- units: days
Temporal Range
2000-01-01T00:00:00
2020-12-31T23:59:59
Geographic Extent
75.0000° |
||
-180.0000° |
180.0000° |
|
-57.0000° |