Period: 1999 – 2007
Frequency: 10 days
Data can be accessed here.
Algorithm description: The algorithm employs neural network based inversion of PROSAIL radiative transfer model (Baret et al, 2009). SPOT-VGT data are converted into top of canopy reflectance in nadir direction through four steps: cloud screening, atmospheric correction, BRDF normalisation and temporal compositing. Finally, these reflectance data are used for inversion using neural nets that are trained using simulation ensemble of PROSAIL model.
Accuracy: Limited information is available on verification of this product. It shows overall underestimation as noted by Baret et al. (2014) based on literature search.
- Limited information is available about product verification.
- Product is available only until 2007
Baret, F. et al. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION Part 1: Principles of the algorithm. Remote Sens. Environ. 110, 275–286 (2007).
Baret, F. & Weiss, M. Algorithm Theorethical Basis Document: LAI, FAPAR, FCOVE, NDVI-Version 1. 1–51 (2014).