Caractérisation de l'émissivité des surfaces terrestres à partir de données multispectrales en infrarouge médian et thermique
Evaluating the potential of middle wave and long wave infrared emissivity for land surface characterization is the challenge of many researches. It remains a topical research subject with the arrival of new remote sensing products giving spectral emissivity images with a large spatial cover. First, we propose a sensitivity analysis of the Temperature Emissivity Separation algorithm (TES) developed for the ASTER sensor and that we adapted for ground based radiometric measurements. The empirical relationship between minimum emissivity and spectral emissivity contrast, on which the TES is based, was validated for 3 and 5 band radiometers in the thermal infrared, with a large dataset. According to our digital simulations, it is possible to derive emissivity and temperature with an accuracy of 0,03 and 1.2K respectively. Secondly, emissivities provided by ASTER (TES algorithm) and MODIS (based on 2 different algorithms,"Classification based emissivity method" and"Day/Night land surface temperature algorithm") were compared for images over northern Canadian regions.--Résumé abrégé par UMI.