NASA’s Mars 2020 Mission is to study Mars’ habitability and seek signs of past microbial life. The mission uses an X-ray fluorescence spectrometer to identify chemical elements at sub-millimeter scales of the Mars surface. The instrument captures high spatial resolution observations comprised of several thousand individual measured points by raster-scanning an area of the rock surface. This paper will show how different methods, including linear regression, k-means clustering, image segmentation, similarity functions, and Euclidean distances, perform when analyzing datasets provided by the X-ray fluorescence spectrometer to assist scientists in understanding the distribution and abundance variations of chemical elements making up the scanned surface. We also created an interactive map to correlate the x-ray spectrum data with a visual image acquired by an RBG camera.


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    Titel :

    Modeling Data of Planetary Instrument for X-ray Lithochemistry (PIXL) for Mars 2020


    Beteiligte:
    Eng, Albert (Autor:in) / Hamalainen, Rimma (Autor:in) / Tran, Tomothy (Autor:in) / Cruz, Gerry (Autor:in) / Nhut, Ho (Autor:in) / Davidoff, Scott (Autor:in) / Liu, Li (Autor:in)


    Erscheinungsdatum :

    01.07.2023


    Format / Umfang :

    7060853 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch