Matching Items (3)
Description
As an example of "big data," we consider a repository of Arctic sea ice concentration data collected from satellites over the years 1979-2005. The data is represented by a graph, where vertices correspond to measurement points, and an edge is inserted between two vertices if the Pearson correlation coefficient between them exceeds a threshold. We investigate new questions about the structure of the graph related to betweenness, closeness centrality, vertex degrees, and characteristic path length. We also investigate whether an offset of weeks and years in graph generation results in a cosine similarity value that differs significantly from expected values. Finally, we relate the computational results to trends in Arctic ice.
ContributorsDougherty, Ryan Edward (Author) / Syrotiuk, Violet (Thesis director) / Colbourn, Charles (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The Jovian moon Europa's putative subsurface ocean offers one of the closest astrobiological targets for future exploration. It’s geologically young surface with a wide array of surface features aligned with distinct surface composition suggests past/present geophysical activity with implications for habitability. In this body of work, I propose a hypothesis for material transport from the ocean towards the surface via a convecting ice-shell. Geodynamical modeling is used to perform numerical experiments on a two-phase water-ice system to test the hypotheses. From these models, I conclude that it is possible for trace oceanic chemistry, entrapped into the newly forming ice at the ice-ocean phase interface, to reach near-surface. This new ice is advected across the ice-shell and towards the surface affirming a dynamical possibility for material transport across the ice-ocean system, of significance to astrobiological prospecting. Next, I use these self-consistent ice-ocean models to study the thickening of ice-shell over time. Europa is subject to the immense gravity field of Jupiter that generates tidal heating within the moon. Analysis of cases with uniform and localized internal tidal heating reveal that as the ice-shell grows from a warm initial ocean, there is an increase in the size of convection cells which causes a dramatic increase in the growth rate of the ice-shell. Addition of sufficient amount of heat also results in an ice-shell at an equilibrium thickness. Localization of tidal heating as a function of viscosity controls the equilibrium thickness. These models are then used to understand how compositional heterogeneity can be created in a growing ice-shell. Impurities (e.g. salts on the surface) that enter the ice-shell get trapped in the thickening ice-shell by freezing. I show the distribution pattern of heterogeneities that can form within the ice-shell at different times. This may be of potential application in identifying the longevity and mobility of brine pockets in Europa's ice-shell which are thought to be potential habitable niches.
ContributorsAllu Peddinti, Divya (Author) / McNamara, Allen Keith (Thesis advisor) / Garnero, Edward (Committee member) / Desch, Steven (Committee member) / Zolotov, Mikhail (Committee member) / Clarke, Amanda (Committee member) / Arizona State University (Publisher)
Created2017
Description
Recent satellite and remote sensing innovations have led to an eruption in the amount and variety of geospatial ice data available to the public, permitting in-depth study of high-definition ice imagery and digital elevation models (DEMs) for the goal of safe maritime navigation and climate monitoring. Few researchers have investigated texture in optical imagery as a predictive measure of Arctic sea ice thickness due to its cloud pollution, uniformity, and lack of distinct features that make it incompatible with standard feature descriptors. Thus, this paper implements three suitable ice texture metrics on 1640 Arctic sea ice image patches, namely (1) variance pooling, (2) gray-level co-occurrence matrices (GLCMs), and (3) textons, to assess the feasibly of a texture-based ice thickness regression model. Results indicate that of all texture metrics studied, only one GLCM statistic, namely homogeneity, bore any correlation (0.15) to ice freeboard.
ContributorsWarner, Hailey (Author) / Cochran, Douglas (Thesis director) / Jayasuria, Suren (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Electrical Engineering Program (Contributor)
Created2024-05