24 February 2004 Global mapping of vegetation parameters from SEVIRI/MSG data
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In this work we present an innovative method for retrieving vegetation variables whilst at the same time making optimal use of the new generation satellite sensors. The approach is aimed to the generation of vegetation products exploding the angular capabilities provided by the MSG/SEVIRI and EPS/AVHRR within the LSA SAF Project. The products include leaf area index (LAI) and fractional vegetation cover (FVC). The algorithm is based on the complementary use of Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) and the inversion of a light-canopy interaction model, namely DISMA (DIrectional Spectral Mixture Analysis), which combines the geometric optics of large scale canopy structure with principles of radiative transfer for volume scattering within individual crowns. Unlike VMESMA, DISMA fully accounts for additional information on directional anisotropy. The prototype has been implemented in the LSA SAF system and tested using SEVIRI synthetic data. The algorithm validation includes feasibility analyses, sensitivity assessments as well as evaluation of the prototype on SEVIRI synthetic data. The study contributes to assess the uncertainties with SEVIRI based vegetation products.
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F. Javier Garcia-Haro, F. Javier Garcia-Haro, Fernando Camacho-de Coca, Fernando Camacho-de Coca, Joaquin Melia, Joaquin Melia, } "Global mapping of vegetation parameters from SEVIRI/MSG data", Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); doi: 10.1117/12.511046; https://doi.org/10.1117/12.511046

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