Matching Items (5)
Filtering by
- All Subjects: Geography
Spatial-Temporal Analysis of Barrett Freshmen 2007-2012: Source Area Analysis and Poisson Regression
Description
In order to help enhance admissions and recruiting efforts, this longitudinal study analyzed the geographic distribution of matriculated Barrett freshmen from 2007-2012 and sought to explore hot and cold spot locations of Barrett enrollment numbers using geographic information science (GIS) methods. One strategy involved   weighted mean center and standard distance analyses for each year of data for non-resident (out-of-state) freshmen home zip codes. Another strategy, a Poisson regression model, revealed recruitment "hot and cold spots" across the U.S. to project the expected counts of Barrett freshmen by zip code. This projected count served as a comparison for the actual admissions data, where zip codes with over and under predictions represented cold and hot spots, respectively. The mean center analysis revealed a westward shift from 2007 to 2012 with similar distance dispersions. The Poisson model projected zero-student zip codes with 99.2% accuracy and non-zero zip codes with 73.8% accuracy. Norwalk, CA (90650) and New York, NY (10021) represented the top out-of-state cold spot zip codes, while the model indicated that Chandler, AZ (85249) and Queen Creek, AZ (85242) had the most in-state potential for recruitment. The model indicated that more students have come from Albuquerque, NM (87122) and Aurora, CO (80015) than anticipated, while Phoenix, AZ (85048) and Tempe, AZ (85284) represent in-state locations with higher correlations between the variables included, especially regarding distance decay, and the than expected numbers of freshmen. The regression also indicated the existence of strong likelihood of attracting Barrett students.
ContributorsKostanick, Megan Elizabeth (Author) / Rey, Sergio (Thesis director) / Dorn, Ron (Committee member) / Koschinsky, Julia (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Politics and Global Studies (Contributor)
Created2013-05
Description
The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde River Watershed. This Story Map is intended for an audience of students in late middle school and early high school but can be a resource to teachers for a wider age range. The integration of interactive technology and virtual tools in educational practices is likely to continue past the immediate circumstances of the COVID-19 pandemic. The purpose of this Story Map is to showcase one of the many uses for geospatial web applications beyond the immediate realm of GIS.
ContributorsTueller, Margaret (Author) / Frazier, Amy (Thesis director) / Dorn, Ron (Committee member) / School of Geographical Sciences and Urban Planning (Contributor, Contributor, Contributor) / Division of Teacher Preparation (Contributor) / The Design School (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Wildfire is a significant risk to property and people in the state of California. In 2018 alone, California's wildfire damages were estimated to be $148.5 Billion or 1.5% of the state's gross domestic product. Wildfire risks to property and people are at their highest at the intersection of flammable wildland vegetation and the built environment, a space called the Wildland Urban Interface or “WUI”. Existing methods for delineating the WUI, however, tend to be coarse in both spatial and temporal resolution, resulting in less precise estimates of WUI extent and change. This thesis uses high-resolution spatio-temporal data and classification methods to remap the WUI in California and to reassess the risk of residents and homes to wildfire. The findings from this analysis reveal that approximately $1.34 Trillion or 40% of the improved residential property value in the state falls within high wildfire risk areas. Likewise, areas classified as WUI account for over 10% of California's land area or a total of 43,205 square kilometers. While WUI areas cover a considerable portion of the state, the addition of a temporal element in this research shows WUI growth in California has slowed considerably over the past 10 years. The unique structure-level data integration strategy applied in this thesis provides a streamlined and expandable process for monitoring the WUI, enabling these new estimates of the hazard risk profiles of areas, structures, and people.
ContributorsBerg, Aleksander K (Author) / Connor, Dylan (Thesis advisor) / Kedron, Peter (Thesis advisor) / Bagchi-Sen, Sharmistha (Committee member) / Frazier, Amy (Committee member) / Arizona State University (Publisher)
Created2022
Description
With the acceleration of urbanization in many parts of the world, transportation challenges such as traffic congestion, increasing carbon emissions, and the “first/last-mile” connectivity problems for commuter travel have arisen. Transport experts and policymakers have proposed shared transportation, such as dockless e-scooters and bike-sharing programs, to solve some of these urban transportation issues. In cities with high population densities, multimodal mobility hubs designed to integrate shared and public transportation can be implemented to achieve faster public connections and thus increase access to public transport on both access and egress sides. However, haphazard drop-offs of these dockless vehicles have led to complaints from community members and motivated the need for neighborhood-level parking areas (NLPAs). Simultaneously, concerns about the equitable distribution of transportation infrastructure have been growing and have led to the Biden Administration announcing the Justice40 Initiative which requires 40% of certain federal investments to benefit disadvantaged communities. To plan a system of NLPAs to address not only the transportation shortcomings while elevating these recent equity goals, this thesis develops a multi-objective optimal facility location model that maximizes coverage of both residential areas and transit stations while including a novel constraint to satisfy the requirements of Justice40. The model is applied to the City of Tempe, Arizona, and uses GIS data and spatial analyses of the existing public transportation stops, estimates of transit station boardings, population by census block, and locations of disadvantaged communities to optimize NLPA location. The model generates Pareto optimal tradeoff curves for different numbers of NLPAs to find the non-dominated solutions for the coverage of population nodes and boardings. The analysis solves the multi-objective model with and without the equity constraint, showing the effect of considering equity in developing a multimodal hub system, especially for disadvantaged communities. The proposed model can provide a decision support tool for transport and public authorities to plan future investments and facilitate multimodal transport.
ContributorsQuan, Hejun (Author) / Kuby, Michael (Thesis advisor) / Frazier, Amy (Thesis advisor) / Tong, Daoqin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Remote sensing, with its capacity to capture continuous, high spatial and spectral resolution data, has emerged as an invaluable tool for ecological research and addressing conservation challenges. To fully harness the potential of remote sensing, spectral ecology has emerged as a field that investigates the interactions between the electromagnetic spectrum and biological processes. This dissertation capitalizes on a model system to explore the spectral ecology of a dominant, highly polymorphic, keystone, and endemic tree species (Metrosideros polymorpha). M. polymorpha not only serves as a model organism for studying adaptive radiation and intraspecific variation but also presents a critical conservation challenge. The recent introduction of the fungal disease Ceratocystis lukuohia has resulted in millions of M. polymorpha mortalities. This dissertation employs leaf-level spectroscopy data and canopy-level imaging spectroscopy data. Imaging spectroscopy captures reflectance across the visible to short-wave infrared (VSWIR) spectrum to provide high-spectral resolution data that enable canopy trait retrievals, species classifications, disease resistance detection, and genotype differentiation. Chapter 1 serves as an introduction, framing the subsequent chapters by presenting an overview of spectral ecology, imaging spectroscopy, and M. polymorpha. Chapter 2 explores M. polymorpha trait and spectra variation across environmental gradients. This chapter concludes that intraspecific variation follows the leaf economic spectrum and that elevation is a dominant driver of M. polymorpha trait and spectral variation. In Chapter 3, leaf-level spectroscopy was able to discriminate between sympatric, conspecific varieties of M. polymorpha and their hybrids as well as individuals resistant and susceptible to Ceratocystis wilt. Together, Chapters 2 and 3 support the concept of “genetic turnover,” akin to species turnover, wherein environmental conditions filter M. polymorpha genotypes present in a given region. Chapter 4 classifies M. polymorpha across the over 10,000 km2 of Hawai'i Island to aid in conservation efforts, demonstrating the potential of imaging spectroscopy to classify vegetation on large geographic scales. The final chapter builds on the prior chapters to present a M. polymorpha genetic diversity map for Hawai'i Island. In conclusion, this dissertation examines the spectral ecology of a model system to advance the understanding of ecological dynamics and address a pressing conservation challenge.
ContributorsSeeley, Megan (Author) / Asner, Gregory P (Thesis advisor) / Turner II, Billie L (Thesis advisor) / Martin, Roberta E (Committee member) / Frazier, Amy (Committee member) / Arizona State University (Publisher)
Created2023