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Dataset

 

ESA Vegetation Parameters Climate Change Initiative (Vegetation_Parameters_cci): LAI and fAPAR, Version 1.0

Update Frequency: Not Planned
Latest Data Update: 2023-11-15
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2023-12-18
DOI Publication Date: 2023-12-18
Download Stats: last 12 months
Dataset Size: 54.01K Files | 263GB

Abstract

Climate Research Data Package 1 from the ESA Climate Change Initiative Vegetation Parameters Project (Vegetation_parameters_cci). The dataset consists of 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 SPOT4/5-VEGETATION1/2 and PROBA-V as input data.

LAI 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, 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-days window. The data are not smoothed in time. The transect is ordered in tiles following the PROBA-V tiling definition. 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 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.

Further details about the data, including validation and intercomparison with similar datasets, can be found in the PDF documentation.

Citable as:  Swinnen, E.; Van der Tol, C.; Blessing, S.; Camacho, F.; Giering, R.; Jolivet, D.; Martínez-Sánchez, E.; Ramon, D.; Sánchez-Zapero, J.; Toté, C.; Vanhoof, K. (2023): ESA Vegetation Parameters Climate Change Initiative (Vegetation_Parameters_cci): LAI and fAPAR, Version 1.0. NERC EDS Centre for Environmental Data Analysis, 18 December 2023. doi:10.5285/34e4bfe402c048c783e64eac0f0bca37. https://dx.doi.org/10.5285/34e4bfe402c048c783e64eac0f0bca37
Abbreviation: Not defined
Keywords: ESA, CCI, Vegetation, LAI, fAPAR, climate change, GCOS

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
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:
The data are provided in netCDF format.

Citations: 1

The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.

Blessing, S., Giering, R. & van der Tol, C. (2024) OptiSAIL: A system for the simultaneous retrieval of soil, leaf, and canopy parameters and its application to Sentinel-3 Synergy (OLCI+SLSTR) top-of-canopy reflectances. Science of Remote Sensing 10, 100148. https://doi.org/10.1016/j.srs.2024.100148 https://doi.org/10.1016/j.srs.2024.100148

Process overview

This dataset was generated by a combination of instruments deployed on platforms and computations as detailed below.

Instrument/Platform pairings

VEGETATION-1 Deployed on: SPOT-4
VEGETATION-2 Deployed on: SPOT-5
Végétation-P Deployed on: PROBA-V

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
  • long_name: coordinate reference system
  • 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
  • long_name: latitude
  • var_id: lat
  • units: degrees_east
  • standard_name: longitude
  • long_name: longitude
  • var_id: lon
  • standard_name: time
  • var_id: time
  • units: days
Coverage
Temporal Range
Start time:
2000-01-01T00:00:00
End time:
2020-06-30T23:59:59
Geographic Extent

 
75.0000°
 
-180.0000°
 
180.0000°
 
-57.0000°