Automatic Detection of H2o and Co2 Ices in Omega/mex Images for the Monitoring of the South Polar Cap Recession
نویسندگان
چکیده
The high latitudes of Mars are covered by a seasonal CO2 ice deposit. The time and space evolutions of this cover is a major annual climatic signal both at the global and the regional scales. In particular the measurement of the temporal and spatial distributions of CO2 constrains many atmospheric and surface processes involving the latter compound but also H2O and dust. The hyperspectral imaging spectrometer OMEGA on board Mars Express has been scrutizing the seasonal changes at the surface of Mars in the near infrared in both hemispheres since it began its operation in early January 2004. OMEGA produces hundreds to thousand images a year, each one made up of thousand to million spectra. Such huge hyperspectral datasets must be analysed by efficient yet accurate algorithms. Thus we propose to use wavanglet, an algorithm particularly suitable for the automatic detection of the spectral signatures characteristics of H2O and/or CO2 ices. This paper presents results obtained by applying wavanglet on a temporal series of images covering the southern hemisphere during the martian spring and summer of 2005 (between Ls=242 and Ls=282). In particular, the detection masks built by the algorithm for each image allows us to draw automatically, as a function of time, the defrost line the line that separates the regions still mantled by frost from those that have lost their icy cover.
منابع مشابه
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