The retrieval methodology, defined by CREAF, is based on neural networks first trained with a combination of existing CYCLOPES and MODIS products to estimate LAI, FAPAR and FCover from daily top of Canopy reflectance. In a second step, temporal techniques are then applied to filter, smooth, fill gaps and get a composited value every 10 days. The quality of the GEOV2 products was assessed by EOLAB. The results show that GEOV2 products keep a high consistency with the previous version 1 (GEOV1, Baret et al., 2013) with 90% of residuals within ± max(0.5, 20%) LAI and 80% within ± max(0.05, 10%) FAPAR / FCover. Furthermore, GEOV2 improves in terms of product completeness (<1% of missing data), temporal consistency, consistency across variables and accuracy.
The details of the algorithm can be found in the Algorithm Theoretical Basis Document while the validation procedure and complete results are available in two quality assessment reports, one for the SPOT/VEGETATION GEOV2 products and one for the PROBA-V GEOV2 products. The three documents are available in the Technical Library while the GEOV2 products are accessible via the Portfolio of the CLMS.
From July 2020 onwards, the production of global LAI, FAPAR, FCover is ensured in the CLMS using the Sentinel-3 OLCI data at 300m resolution. The products are available in near-real-time every 10 days. The retrieval methodology is similar to GEOV2 approach and the products are consistent with the historical GEOV2 products, as demonstrated in Fuster et al., 2020.
Verger, A., J. Sanchez-Zapero, M. Weiss, A. Descals, F. Camacho, R. Lacaze and F. Baret. GEOV2: improved smoothed and gap filled time series of LAI, FAPAR and FCover 1km Copernicus Global Land products, International Journal of Applied Earth Observation and Geoinformation, vol. 123, Sept. 2023, 103479. https://doi.org/10.1016/j.jag.2023.103479
Baret, F., M. Weiss, R. Lacaze, F. Camacho, H. Makmarra, P. Pacholcyzk and B. Smets. GEOV1: LAI and FAPAR essential climate varaibles and FCover global time series capitalizing over existing products. Part1: principles of development and production, Remote Senging of Environment, vol. 137, October 2013, pages 299-309. https://doi.org/10.1016/j.rse.2012.12.027
Fuster, B., J. Sánchez-Zapero, F. Camacho, V. García-Santos, A. Verger, R. Lacaze, M. Weiss, F. Baret and B. Smets. Quality Assessment of PROBA-V LAI, FAPAR and FCover Collection 300 m Products of Copernicus Global Land Service. Remote Sensing 2020, 12137, 1017. https://doi.org/10.3390/rs12061017
