Social and Behavioral Sciences Commons^™

Automated Identification And Mapping Of Interesting Mineral Spectra In Crism Images, Arun M. Saranathan

Doctoral Dissertations

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has proven to be an invaluable tool for the mineralogical analysis of the Martian surface. It has been crucial in identifying and mapping the spatial extents of various minerals. Primarily, the identification and mapping of these mineral spectral-shapes have been performed manually. Given the size of the CRISM image dataset, manual analysis of the full dataset would be arduous/infeasible. This dissertation attempts to address this issue by describing an (machine learning based) automated processing pipeline for CRISM data that can be used to identify and map the unique mineral signatures present in …

Care Work In Chile’S Segregated Cities, Manuel Garcia

Doctoral Dissertations

This project combines diverse theoretical and methodological tools to examine the relationship between space and care work in Chile. The chapters are stand-alone articles that come together to tell a single story. The social production of urban space has marginalized thousands of female caregivers from the labor market as Chile’s care system unravels. I argue that community caregiving could simultaneously improve the conditions of caregivers and dependents. Chapter 1 examines the role of residential segregation in reproducing Chile’s meager female labor market participation rates. I use spatial and econometric analysis to show that the social forces that segregate Santiago create …

Dynamics Of Collaborative Navigation And Applying Data Driven Methods To Improve Pedestrian Navigation Instructions At Decision Points For People Of Varying Spatial Aptitudes, Gengen He

Doctoral Dissertations

Cognitive Geography seeks to understand individual decision-making variations based on fundamental cognitive differences between people of varying spatial aptitudes. Understanding fundamental behavioral discrepancies among individuals is an important step to improve navigation algorithms and the overall travel experience. Contemporary navigation aids, although helpful in providing turn-by-turn directions, lack important capabilities to distinguish decision points for their features and importance. Existing systems lack the ability to generate landmark or decision point based instructions using real-time or crowd sourced data. Systems cannot customize personalized instructions for individuals based on inherent spatial ability, travel history, or situations.

This dissertation presents a novel experimental …