Prototyping of Land-SAF leaf area index algorithm with VEGETATION and MODIS data over Europe

The Satellite Application Facility on Land Surface Analysis (Land-SAF) aims to provide land surface variables for the meteorological and environmental science communities from EUMETSAT satellites. This study assesses the performance of a simplified (i.e. random distribution of vegetation is assumed) version of the Land-SAF algorithm for the estimation of Leaf Area Index (LAI) when prototyped with VEGETATION (processed in CYCLOPES program) and MODIS reflectances. The prototype estimates of LAI are evaluated both by comparison with validated CYCLOPES and MODIS LAI products derived from the same sensors and directly through comparison with ground-based estimates. Emphasis is given on evaluating the impact of the algorithm and input data on LAI retrieval discrepancies. Analysis is achieved over Europe for the 2000–2003 period. The results demonstrate the capacity of the Land-SAF algorithm to retrieve consistent LAI estimates from multiple optical sensors even when their reflectances present systematic differences. High spatial and temporal consistencies between Land-SAF prototype estimates and existing LAI products are found. The differences between Land-SAF and CYCLOPES LAI are lower than their uncertainties (RMSE (relative RMSE) within 0.4 (30%)). Land-SAF prototype estimates and MODIS LAI show larger discrepancies mainly due to differences in the vegetation structure representation and algorithm assumptions (RMSE ranging from 0.2 (30%) up to 0.8 (40%)). Land-SAF prototype provides higher LAI values than MODIS for herbaceous canopies (i.e. shrubs, grasses and crops) and lower values for woody biomes (i.e. savannas and forests). Direct validation indicates that LAI estimates from prototyping of the Land-SAF algorithm with CYCLOPES and MODIS reflectances achieve similar performances (differences with ground measurements are lower than 0.5 LAI units in 60% and 50% of the cases, respectively) as CYCLOPES and MODIS LAI products. Results from this prototyping exercise appear useful for improved retrieval of LAI and constitute a step forward for refinement, validation and consolidation of the Land-SAF algorithm.