F. Camacho-de Coca

Accuracy assessment of fraction of vegetation cover and leaf area index estimates from pragmatic methods in a cropland area

The fraction of vegetation cover (FVC) and the leaf area index (LAI) are important parameters for many agronomic, ecological and meteorological applications. Several in‐situ and remote sensing techniques for estimating FVC and LAI have been developed in recent years. In this paper, the uncertainty of in‐situ FVC and LAI measurements was evaluated by comparing estimates from LAI‐2000 and digital hemispherical photography (DHP). The accuracy achieved with a spectral mixture analysis algorithm and two vegetation indices‐based methods was assessed using atmospherically corrected Landsat Thematic Mapper (TM) data over the Barrax cropland area where the European Space Agency (ESA) SENtinel‐2 and FLuorescence EXperiment (SEN2FLEX) field campaign was carried out in July 2005. The results indicate that LAI‐2000 and DHP performances are comparable, with uncertainties of 5% for FVC and 15% for effective LAI. The selected remote sensing methods are shown to be consistent, with a notable overall accuracy (root mean square error, RMSE) of 0.07 (10% in relative terms) for FVC and 0.8 (30%) for LAI. Similar bounds were found on upscaling in‐situ measurements with empirical transfer functions (TFs). These results suggest that the pragmatic methods considered applied at high resolution with minimum calibration data could be useful for mapping FVC and LAI in the study area, reducing in‐situ labour‐intensive characterization necessities for validation studies.

Direct validation of FVC, LAI and FAPAR VEGETATION/SPOT derived products using LSA SAF methodology

The aim of this work is to perform a direct validation of fraction of vegetation cover (FVC), leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR) resulting products from applying the LSA SAF methodology to VEGETATION BRDF data. LSA SAF adapted algorithms were tested in adequate test sites comprising different continental biomes covering a wide range of FVC, LAI and FAPAR values. Results seem to indicate the competitiveness of LSA SAF proposed methodology to retrieve remotely sensed biophysical parameters. A noticeable good agreement regarding the ground measurements was found. The overall accuracy (RAISE) is around 20% for FVC and FAPAR and around 15% for LAI.

Prototyping algorithm for retrieving FAPAR using MSG data in the context of the LSA SAF project

This paper describes the prototyping algorithm developed for retrieving the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) using MSG data in the framework of satellite application facility on land surface analysis (LSA SAF). The prototyping relies on the Roujean and Breon (1995) method, which is based on simulations of visible and near infrared reflectance values in an optimal geometry. A relationship is found between a vegetation index and daily FAPAR The algorithm has been applied to one year of MSG BRDF data since August 2005, using a temporal frequency of 5-days, and then validated against a set of operational satellite FAPAR products such as MODIS, MERIS, SeaWiFS and CYCLOPES, as well as with ground-truth information. MSG FAPAR products present a reliable spatial and temporal distribution of retrievals. The inter-comparison of the MSG FAPAR product with different operational products shows the large existing differences among FAPAR products. However, the best consistency is found between MSG and MERIS (only July 2006 was evaluated) or between MSG and CYCLOPES (available only for 2003). At a pixel level, the RMS over selected validation sites is lower than 0.1 between MSG and MERIS or MSG and CYCLOPES products, which demonstrates the competitiveness of the proposed prototype.