Oscar Matthijs Kamps

, MSc

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Global study on Mars using CRISM summary products

For many regions on Mars the surface composition is still debated. Data to validate orbital interpretations of the composition are rare, therefore new approaches are required to get a consensus on the global composition. In this PhD-project multivariate data analysis techniques are applied on satellite datasets. Orbital spectral products from the CRISM instrument, measured in the visible-/ near-infrared wavelength range, are used for a multivariate data analysis study. With this dataset surface types on Mars are defined using a clustering method. This way new surface types can be described or previous surface types can be better understood with the information from the spectral parameters. The same products are used for a statistical model to predict the element composition as measured with gamma-ray spectroscopy. This combination should give an insight on what geological process is behind the element distribution. So far, this can only be estimated based on their spatial distribution, but the low resolution of the data makes it difficult to conclude on a process.


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