Structural analysis of interior layered deposits in north and south Coprates Chasma, Mars

Interior layered deposits within an embayment in the northern as well as near the southern wall of Coprates Chasma in the Valles Marineris, Mars are studied using HRSC, CTX, HiRISE and CRISM data. In the northern embayment, layered deposits outcrop in three separate locations (a western deposit, a central deposit and an eastern deposit). The central layered deposit in the north has a stratigraphic thickness of 2 km. The western layered deposit abuts against the chasma wall appearing to have a relatively un-eroded depositional surface. The eastern deposit is near a landslide scar which appears to have exposed basement layering showing downward displacement. This northern embayment is suggested to have been an ancestral basin. The triangular edged deposit near the southern wall of Coprates Chasma has an elongated mound protruding from the central edge and is suggested to be the outer limits of a fault block which is back rotated 6° south. The rotation may be the result of the Valles Marineris opening.

DEFORMATION OF INTERIOR LAYERED DEPOSITS (ILD) AND THEIR ASSOCIATED LANDFORMS IN WEST CANDOR CHASMA, MARS: IMPLICATIONS FOR THE TIMING OF ILD DEPOSITION

On Mars, interior layered deposits (ILD) provide evidence that water was once stable at the surface of the planet and present in large quantities. In West Candor Chasma, the ILD and their associated landforms record the depositional history of the chasma, and the deformation of those deposits provide insight into the stresses acting on them and the chasma as a whole. The post ILD structural history of West Candor is interpreted by analyzing the spatial relationships and orientation trends of structural features within the ILD. Therecording of stresses through brittle deformation of ILDs implies that the ILD had been lithified before the stress was imposed. Based on the prominent orientation trends of deformation features, the orientation of the stress regime acting upon the ILD appears to be linked to the regime that initially created the chasma-forming faults. An additional minor stress orientation was also revealed and may be related to large structures outside west Candor Chasma. The late depositional history of Ceti Mensa is herein investigated by examining the attributes and spatial relationship between unique corrugated, linear formations (CLF). The CLFs appear to be aeolian in origin but display clear indications of brittle deformation, indicating they have been Iithified. Evidence of lithification and the mineral composition of the surrounding material support the interpretation of circulating water in the area.

Hyperspectral Mineral Identification using SVM and SOM

Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).