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CRISM sensor - available data and possible applications for mineral detection on Mars
Pavlová, Martina ; Červená, Lucie (advisor) ; Potůčková, Markéta (referee)
This bachelor's thesis focuses on data accumulated by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) sensor and the possibilities of their subsequent processing. The first part of this paper focuses on the history of remote sensing of Mars since its beginning in the 1960s, with the most detailed description of the Mars Reconnaissance Orbiter (MRO) mission which carries the CRISM spectroradiometer. The nine different data products acquired by this instrument are described in detail together with the possibilities of their download and subsequent processing. Furthermore, the minerals found on the surface of Mars are mentioned and examples of their spectral curves are shown. In the practical part, the processing of CRISM data in JCAT is first presented, from the actual data download to the creation of spectral curves suitable for comparison with spectral libraries. Subsequently, an image containing low calcium pyroxene was selected. This image was preprocessed in CAT in ENVI and using three different methods which were Linear Spectral Unmixing (LSU), Spectral Angle Mapper (SAM) and spectral parameter calculation, the detection of the selected mineral was performed. The LSU and SAM methods gave similar results, but the calculation of spectral parameters differed more from them, which...
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Remote Sensing of the Icy Moons of Jupiter - Galileo mission
Tomášková, Eliška ; Červená, Lucie (advisor) ; Potůčková, Markéta (referee)
The bachelor's thesis focuses on the processing and analysis of Galileo SSI and NIMS image data, which captures the Tyre region of Europa and the Kittu region of Ganymede. Initially, the problems of data retrieval from the PDS archive and its thorough radiometric and geometric corrections are addressed. Pre-processing, visualization, and subsequent data analysis were conducted using the POW tool, ISIS3, ENVI, and ArcGIS Pro software. Based on the principal component analysis of the NIMS data, the two most different end-members representing ice and "salt" were selected. These were then used in Linear Spectral Unmixing, which provided information on the spatial distribution and relative concentrations of the "salt" end-member in the study areas. The outputs from the hyperspectral data were projected over the higher spatial resolution data to examine relationships between surface morphology and composition. The resulting SSI, Voyager, and NIMS composites suggest a strong correlation between the salt component and areas with disrupted ice crust on Jupiter's icy moons. Furthermore, unsupervised classification of SSI images capturing the Tyre crater was performed and showed similar results to Linear Spectral Unmixing of the NIMS data. Additionally, significant differences in reflectance values between...
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Classification of Norway Spruce based on imaging and laboratory spectroscopy
Soudková, Kristýna ; Potůčková, Markéta (advisor) ; Kupková, Lucie (referee)
The master thesis deals with subpixel classification of hyperspectral data from senzor APEX. In the first part there is research from the literature describing algorithms of the subpixel classifications and spectral characteristics of the vegetation. In the practical part there is a work focusing on the classification of the areas with the cover of Norway Spruce trees at eight areas in the Krkonoše national park. Three methods of supervised classification were used - Linear Spectral Unmixing, Support Vector Machine and Spectral Angle Mapper. Field data, spectral curves for exact trees from the eight areas obtained by the contact probe ASD FieldSpec 4 Wide-Res, were used for the extraction of endmembers of the spruces. For each research area maps of land cover were produced by means of the classification methods described above and the accuracies of the classifications were evaluated. Powered by TCPDF (www.tcpdf.org)
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Classification of Norway Spruce based on imaging and laboratory spectroscopy
Soudková, Kristýna ; Potůčková, Markéta (advisor) ; Kupková, Lucie (referee)
The master thesis deals with subpixel classification of hyperspectral data from senzor APEX. In the first part there is research from the literature describing algorithms of the subpixel classifications and spectral characteristics of the vegetation. In the practical part there is a work focusing on the classification of the areas with the cover of Norway Spruce trees at eight areas in the Krkonoše national park. Three methods of supervised classification were used - Linear Spectral Unmixing, Support Vector Machine and Spectral Angle Mapper. Field data, spectral curves for exact trees from the eight areas obtained by the contact probe ASD FieldSpec 4 Wide-Res, were used for the extraction of endmembers of the spruces. For each research area maps of land cover were produced by means of the classification methods described above and the accuracies of the classifications were evaluated. Powered by TCPDF (www.tcpdf.org)
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