Intercomparison Approach QUALITY ASSESSMENT METHOD

ground reference maps to quantify the overall uncertainties of the products.

2.1 Intercomparison Approach

The reference global satellite products used are: GEOV1 based on SPOTVGT observations Baret et al., 2013 and Terra MODIS LAIFAPAR MOD15A2 collection 5 Knyazikhin et al., 1998. The products were intercompared over the BELMANIP2.1 Weiss et al., 2014 network of sites that was designed to represent globally the variability of land surface types. Furthermore, the products are analysed for 6 generic classes, namely: Evergreen Broadleaf Forest, Evergreen Deciduous Forest, Needle-leaf Forest, Croplands, Herbaceous and ShrubSparseBare Areas. The different products must be compared over a similar spatial support area and temporal support period. The intercomparison was conducted using an average value over 3x3 pixels to reduce coregistration errors between products and differences in their sensor Point Spread Function PSF which determines the actual footprint of the data. The temporal support period for the quantitative assessment is 10-days with monthly composites. The original temporal sampling was used for compute missing values, histograms and the smoothness. The following criteria of performance and metrics are assessed:  Product Completeness: corresponds to the absence of spatial and temporal gaps in the data. Temporal variations of GEOV1 missing values for SPOTVGT and PROBA-V LAI products have been computed over the whole images.  Spatial Consistency: can be quantitatively assessed by comparing the spatial distribution of a reference validated product with the product under study. Global histograms of residuals at a monthly basis were analyzed. This analysis is complemented by the analysis of Probability Density Function PDFs of retrievals per biomes.  Temporal Consistency: The consistency of temporal variations of the vegetation variables are qualitatively analyzed as compared to reference validated products.  Intra-annual precision smoothness: corresponds to temporal noise assumed to have no serial correlation within a season. In this case, the anomaly of a product LAI value from the linear estimate based on its neighbors can be used as an indication of intra-annual precision or smoothness. It can be characterized as suggested by Weiss et al., 2014: for each triplet of consecutive observations, the absolute value of the difference between the center Pdn+1 and the corresponding linear interpolation between the two extremes Pdn and Pdn+2 was computed: 1 Histograms of the smoothness are presented adjusted to a negative exponential function. The exponential decay constant is used as quantitative indicator of the typical smoothness value.  Relative Uncertainties: The inter-comparison of products offers an indirect means of assessing uncertainties systematic or random between products. The global statistical analysis is performed over BELMANIP2.1 sites considering all the dates available.

2.2 Direct Validation