MSG 10-days Leaf Area Index (MTLAI-R, LSA-451)

DOI for scientific and technical data: 



Leaf Area Index (LAI) is a dimensionless variable [m2/m2], which defines an important structural property of a plant canopy. LAI is defined as one half the total leaf area per unit ground area (Chen and Black, 1992). It provides complementary information to the FVC, accounting for the surface of leaves contained in a vertical column normalized by its cross-sectional area. It defines thus the area of green vegetation that interacts with solar radiation determining the remote sensing signal, and represents the size of the interface between the vegetation canopy and the atmosphere for energy and mass exchanges. LAI is thus a necessary input for Numerical Weather Prediction (NWP), regional and global climate modelling, weather forecasting and global change monitoring. Besides, the LAI is relevant for Land Biosphere Applications such us agriculture and forestry, environmental management and land use, hydrology, natural hazards monitoring and management, vegetation-soil dynamics monitoring and drought conditions.


Product Documentation

The characteristics and file format of this released Data Record are the same as its correspondent NRT product. It is documented in the following documents:

Please see Product Peer-Review publications in References.

Here you will find the daily Leaf Area Index averaged per month over the 2004-2019 period.

This dataset was derived by joining the LAI CDR (MDLAI-R) for 2004-2015 and the operational NRT product (MDLAI, LSA-423) for 2016-2019.



This NetCDF file contains the average of daily LAI for all days of "December" over the 2004-2019 period. The datasets are available on a regular 0.05º grid and the files' format is fully CF-compliant.

The use of LSA SAF products in publications is kindly requested to be duly acknowledged:
LAI was provided by the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF; Trigo et al., 2011)

Trigo, I. F., C. C. DaCamara, P. Viterbo, J.-L. Roujean, F. Olesen, C. Barroso, F. Camacho-de Coca, D. Carrer, S. C. Freitas, J. García-Haro, B. Geiger, F. Gellens-Meulenberghs, N. Ghilain, J. Meliá, L. Pessanha, N. Siljamo, and A. Arboleda, 2011: The Satellite Application Facility on Land Surface Analysis. Int. J. Remote Sens., 32, 2725-2744, doi: 10.1080/01431161003743199

The MSG mission (in operations since 2004) already provides a relatively long time series of VIS and IR observations over the full Earth Disk centred at 0º. The full archive of MSG/SEVIRI data was reprocessed to provide the user comunity a consistent, homogeneous and continuous Data Record of the  10-days Leaf Area Index (MTLAI) for the period 2004-2015. 

This Data Record was obtained with the best version of its equivalent NRT product (MTLAI) which can also complement the time series from 2016 onwards.

García-Haro, F. J., Camacho, F., Martínez, B., Campos-Taberner, M., Fuster, B., Sánchez-Zapero, J., & Gilabert, M. A. (2019). Climate data records of vegetation variables from geostationary SEVIRI/MSG data: products, algorithms and applications. Remote Sensing, 11(18), 2103. DOI: 10.3390/rs11182103.

García-Haro, F.J., Camacho-de Coca, F., Meliá, J. (2006). DISMA  A Directional Spectral Mixture Analysis method: Application to multi-angular airborne measurements. IEEE Transactions of Geoscience and Remote Sensing, 44(2), 365-377,  DOI: 10.1109/TGRS.2005.861008.

Roujean, J.L. and R. Lacaze, (2002). Global mapping of vegetation parameters from POLDER multiangular measurements for studies of surface-atmosphere interactions: A pragmatic method and its validation. Journal of Geophysical Research, 107D, 10129-10145.

Chen, J. M. and T. A. Black, 1992. Defining leaf area index for non-flat leaves. Plant Cell Environment, 15: 421-429.