Leaf area index LAI from SPOT/PROBA-V/S3-OLCI
Topics
- Access
- Description
- Parameters
- Coverage, spatial and temporal resolution
- Data quality
- Contact person
- References
- Data citation
Access
RESTRICTED: This link to the data set is only available for a restricted user group. The data set is only accessible in CEN/MPI net or accessible from external nets with a customer account. Please contact ICDC if you would like to access this data from outside the network.
- View LAI data at 0.5 degree grid resolution at LAS Spot/Proba-V | Proba-V/S3 OLCI
- Access LAI data at 0.5 degree grid resolution via OPeNDAP
- Data access (all resolutions) via file system: /data/icdc/land/lai_spot_proba_v
Description
The Leaf Area Index (LAI) is defined as half the total area of photosynthetically active elements (e.g. leaves, needles) of the canopy per unit horizontal ground area. The LAI is a measure of the size of the interface for exchange of energy (including radiation) and mass between the canopy and the atmosphere. The LAI is strongly non-linearly related to reflectance. A satellite-derived LAI value corresponds to the total green LAI of all the canopy layers, including the understory which may represent a very significant contribution, particularly for forests. Practically, one can say that the LAI quantifies the thickness of the vegetation cover. For remote sensing of the LAI it is often assumed that the leaves are randomly distributed within the vegetation volume sensed and hence the retrieved LAI is an "effective" LAI being the best possible approximation of the actual LAI (see also the references).
Top of canopy input reflectance from SPOT-4 & -5, PROBA-V, and - more recently - Sentinel-3 OLCI in various spectral bands (12 for Sentinel-3 OLCI, 3 otherwise), normalized over a period of 30 days are used in a neural network approach. Normalization over the 30-day period us done with a weighting function which favors the most recent daily observations of the compositing period. The neural network is trained with true (non-simulated) reflectance data and LAI estimates from fused existing products based on MODIS and CYCLOPES LAI products. Calibration of the neural network used for Sentinel-3 OLCI data is done with PROBA-V results. Note that "clumping" or "clumpiness" (see Chen et al., 2005 in references), i.e. the degree with which the leaves are not randomly distributed within the vegetation volume sensed, is not part of the data set offered here.
For more information we refer to the ATBDs mentioned in the references section.
We offer various versions of this data set provided by COPERNICUS Global Land Service (see references).
Data were downloaded in netCDF file format with 1/112° (about 1 km) grid resolution (SPOT / PROBA-V) and 1/336° (about 1/3 km) grid resolution (PROBA-V / Sentinel-3 3OLCI) at global coverage. These data are available at ICDC. In addition we offer a block-averaged version of the SPOT / PROBA-V 1/112° data and the PROBA-V / S3-OLCI 1/336° data at a 0.5° x 0.5° plate carree grid. Data are available for the latitude range 70°S to 80°N (60°S to 75°N for PROBA-V / S3-OLCI). Note, however, that limited solar illumination reduces the maximum northern latitude to smaller values during winter.
Last update of data set at ICDC: March 21, 2024.
Parameters
| Name | Unit/Range | Comment | 0.5° | 1/112° | 1/336° |
|---|---|---|---|---|---|
| Leaf area index (LAI) | 0 ... 7 (m²/m²) | resolution is 1/30 | x | x | x |
| LAI uncertainty | 0 ... 7 (m²/m²) | resolution is 1/30 (This is the RMSE between 10-day composit & daily values) | x | x | x |
| Number of land pixels | 0 ... 3136 ... 28224 | per 0.5° grid cell (see information in netCDF file) | x | ||
| Number of valid data pixels | 0 ... 3136 ... 28224 | per 0.5° grid cell / 1/112° pixel or / 1/336° pixel (see information in netCDF file) | x | x | x |
| Mean number of usable satellite data | 0 ... 120 | per 0.5° grid cell | x | ||
| Cumulative number of usable satellite data | 0 ... 188160 ... 1693440 | per 0.5° grid cell | x | ||
| Number of days included before the data of the product | 0 ... 60 days | x | x | ||
| Number of days included after the data of the product | 0 ... 60 days | x | x | ||
| Bitwise quality flag | 0 ... 255 | x | x | ||
| Surface type flag | 1, 10, 20, 40 |
Dominant (major) surface type: See the respective information about the flag values and their meaning in the netCDF file |
x |
||
| (Primary) Retrieval flag | 0 ... 24 (... 114) |
Dominant (major) retrieval type: See the respective information about the flag values and their meaning in the netCDF file |
x |
||
| Secondary retrieval flag (PROBA-V / S3-OLCI) | 0 ... 114 |
Second most retrieval type: See the respective information about the flag values and their meaning in the netCDF file |
x |
Coverage, spatial and temporal resolution
Period and temporal resolution:
- 1998-11-10 to 2020-04-30 (SPOT/PROBA-V) 2014-01-10 to 2023-12-31 (PROBA-V/S3-OLCI)
- 10-daily sampling, 60-day effective resolution
Coverage and spatial resolution:
- Global
- Spatial resolution: 0.5° x 0.5° and 1/112° x 1/112° (SPOT/PROBA-V), 0.5° x 0.5° and 1/336° x 1/336° (PROBA-V/S3-OLCI)
- Geographic latitude: 90°S to 90°N and 70°S to 80°N (75°N)
- Geographic longitude: 180°W to 180°E
- Dimension: 360 rows x 720 columns and 15680 rows x 40320 columns (47040 rows x 120960 columns)
- Altitude: follows topography
Format:
- NetCDF
Data quality
The data sets at 1/112° and 1/336° grid resolution contain a bit-wise to read quality flag. The content of the flag can be read at the Leaf Area Index | Copernicus Global Land Service Website under the tab "Technical" (see references).
The 0.5° x 0.5° data set offered in addition contains two basic separate flags. One flag refers to the two surface types where LAI 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 the number of valid 1/112° x 1/112° or 1/336° x 1/336° grid points used to compute the average value of the LAI and its uncertainty is given. 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. Note that we excluded LAI data where the average (over the 0.5° x 0.5° grid cell) relative error is larger than 50% in SPOT/PROBA-V.
LAI products have been validated and inter-compared with independent observations - globally, regionally. for different biomes, and also with regard to the temporal development - 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. More information about the validation efforts can be found in the validation reports listed under references.
We note that the PROBA-V/S3-OLCI data set contains jumps in the values when switching from combined PROBA-V/S3-OLCI to pure S3-OLCI between June 2020 and July 2020.
Contact
Frederic Baret
Institut National de la Recherche Agronomique (INRA), France
email: frederic.baret (at) avignon.inra.frBruno Smets
VITO, Belgium
email: Bruno.Smets (at) vito.beStefan Kern
University of Hamburg
email: stefan.kern (at) @uni-hamburg.de
References
Literature:
- ATBD PROBA2VG, Gio Global Land Component -Lot I”, Operation of the Global Land Component”Framework Service Contract N° 388533 (JRC), ALGORITHM THEORETHICAL BASIS DOCUMENT, PROBA2VG, TPRE-PROCESSING (pdf, not barrier free)
- Algorithm Theoretical Basis Document: ATBD_v2_issueI1.41 (pdf, not barrier free)
- Product User Guide for Version 2: PUM_v2_issue1.33 (pdf, not barrier free)
- Validationsreport for SPOT QAR_v2_issueI2.01 (pdf, not barrier free)
- Validationsreport for PROBA-V: QAR_v2_issueI1.40 (pdf, not barrier free)
- Scientific Quality Evaluation for version 1 & 2: SQE2018_v1v2_issueI1.00 (pdf, not barrier free)
- Scientific Quality Evaluation - Cross-cutting consistency: SQE2018_CCR_issueI1.00 (pdf, not barrier free)
- Baret, F., Weiss, M., Lacaze, R., Camacho, F., Makhmara, H., Pacholczyk, P., and Smets, B. (2013), GEOV1: LAI, FAPAR Essential Climate Variables and FCover global times series capitalizing over existing products. Part1: Principles of development and production. Remote Sensing of Environment, 137, 299–309.
- Baret, F., Hagolle, O., Geiger, B., Bicheron, P., Miras, B., Huc, M., Berthelot, B., Weiss, M., Samain, O., Roujean, J. L. et al. (2007), LAI, fAPAR and fapar CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm. Remote Sensing of Environment, 110, 275-286.
- Camacho, F., Cernicharo, J., Lacaze, R., Baret, F., and Weiss, M. (2013), GEOV1: LAI, FAPAR Essential Climate Variables and FCover global time series capitalizing over existing products. Part 2: Validation and inter-comparison with reference products. Remote Sensing of Environment, 137, 310-329.
- Verger, A., Baret, F., and Weiss, M. (2014), Near real-time vegetation monitoring at global scale. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 3473-3481.
- Chen, J. M., Menges, C. H., and Leblanc, S. G. (2005), Global mapping of foliage clumping index using multi-angular satellite data. Remote Sensing of Environment, 97(4), 447-457.
- Tote, C., Swinnen, E., Sterckx, S., and 10 others (2018), Evaluation of PROBA-V Collection 1: Refined Radiometry, Geometry, and Cloud Screening. Remote Sensing, 10(9), 1375, http://doi.org/10.3390/rs10091375
- Munier, S., Carrer, D., Planque, C., Camacho, F., Albergel, C., and Calvet, J.-C. (2018), Satellite leaf area index: global scale analysis of the tendencies per vegetation type over the last 17 years. Remote Sensing, 10(3), 424, http://doi.org/10.3390/rs10030424
- Jiang, C., et al., 2017, Inconsistencies of interannual variability and trends om long-term satellite leaf-area index products. Global Change Biology, 23, 4133-4146, doi: 10.1111/gcb.13787.
Websites:
- Leaf Area Index | Copernicus Global Land Service, http://land.copernicus.eu/global/products/lai
Data citation
Please cite the data 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
SPOT/PROBA-V: 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 LAI 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) [when using the coarse-resolution data: provided on 0.5 degree x 0.5 degree plate carree grid] [last access date: August 26, 2020] in netCDF file format by the Integrated Climate Data Center (ICDC) University of Hamburg, Hamburg, Germany.
PROBA-V/S3-OLCI: The product was generated by the global component of the Land Service of Copernicus, the Earth Observation program 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 programs. The product is based on PROBA-V and Sentinel-3 data (© ESA) [when using the coarse-resolution data: provided on 0.5 degree x 0.5 degree plate carree grid] [last access: March 15 2024] in netCDF file format by the Integrated Climate Data Center (ICDC) University of Hamburg, Hamburg, Germany.