In this work we present some results concerning the analysis of Thermal Emission Spectrometer (TES) data, looking at the methane Q-branch spectral signature at 1304 cm-1. Such analysis has been enabled by producing some synthetic spectral datasets, simulating the atmospheric and surface variability observed on Mars, excluding the high latitude regions. The use of synthetic spectra is aimed to provide a better comprehension of the influence that the atmospheric state vector and its composition have on the spectral behavior. This effort is important, because the TES data are characterized by a low resolution (10 cm-1) and a significant random and systematic noise which could, in principle, give results whose quality needs to be improved. We apply statistical clustering of the synthetic spectra to evaluate the effectiveness of detecting methane, and estimating its abundance.
Validation of statistical clustering on TES dataset using synthetic Martian spectra
LIUZZI, GIULIANO;MASIELLO, Guido;SERIO, Carmine;
2014-01-01
Abstract
In this work we present some results concerning the analysis of Thermal Emission Spectrometer (TES) data, looking at the methane Q-branch spectral signature at 1304 cm-1. Such analysis has been enabled by producing some synthetic spectral datasets, simulating the atmospheric and surface variability observed on Mars, excluding the high latitude regions. The use of synthetic spectra is aimed to provide a better comprehension of the influence that the atmospheric state vector and its composition have on the spectral behavior. This effort is important, because the TES data are characterized by a low resolution (10 cm-1) and a significant random and systematic noise which could, in principle, give results whose quality needs to be improved. We apply statistical clustering of the synthetic spectra to evaluate the effectiveness of detecting methane, and estimating its abundance.File | Dimensione | Formato | |
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