UA Graduate and Undergraduate Research: Recent submissions
Now showing items 1-20 of 44207
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Greening the Grid: The Power of Public Awareness and Policy in Advancing Green Infrastructure in HawaiʻiThis research examines green infrastructure (GI) – natural and engineered systems, like trees and permeable pavement – and aims to address its key benefits in mitigating the urban heat island (UHI) effect and lowering excessive energy consumption habits in Honolulu, Hawaiʻi. The UHI effect has created a plague of extreme heat on the densely packed island of Oʻahu due to heat-absorbing materials, like asphalt and concrete, creating a slightly warmer and uncomfortable environment. This effect is creating the need for sustainable, non-traditional strategies, such as GI, to help alleviate the impact of rising temperatures and high energy consumption. However, challenges like limited public awareness, policy support, and maintenance requirements have delayed GI adoption in Honolulu. Through surveys, stakeholder interviews, and secondary data analysis, this study identifies solutions to implementing more GI on the island, including the placement of governmental incentives, better community engagement, and long-term maintenance solutions. A site-specific analysis of Waimalu Plaza in Honolulu, HI is used to evaluate how urban forests could improve energy efficiency and reduce heat exposure in one of the biggest UHI hot spots on the island. The findings from this study suggest that while GI provides numerous benefits, its long-term effects depend on proper maintenance, sufficient financial support, and the help of the community to support its success. The study tells of the benefits and challenges of implementing green infrastructure into Hawaiʻi’s unique environment to create a more sustainable and climate-resilient city.
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Recreational Heat Exposure to Youth Populations in Tucson, ArizonaThe exposure to extreme heat is both an environmental and a social issue. Youth populations are some of the most vulnerable to heat-related illness yet are often omitted in city plans and policies, further increasing their risk of exposure to the adverse impacts of extreme heat. A mixed-methodology approach using social mapping and plan evaluation was used to identify which areas within the greater Tucson area children are most vulnerable to extreme heat. The social mapping process identified a lack of services and areas where youth were particularly vulnerable to heat due to a lack of heat relief areas, like Flowing Wells and southeast Tucson. Evaluation of Tucson’s 2024 Heat Action Roadmap demonstrates the city’s clear mission to address heat resiliency equitably for vulnerable populations. Despite the inclusion of effective heat-specific strategies, very few were specific to youth populations.
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Examining production of municipal solid waste for bulk pickup and median household income in Tucson, ArizonaThe relationship between socioeconomic factors like median household income and behavior tied to the production of bulk waste has important ramifications for improving municipal waste management systems. This study investigates this relationship among different neighborhoods in the city of Tucson, Arizona. Using direct observation methods in 18 neighborhoods of varying income levels within six waste management districts across the city, this study identifies the physical manifestation of the role household income plays in the production of bulk waste. Observation routes were designed in each of the 18 neighborhoods, keeping the number of parcels in each route constant for consistency. Observations recorded the amount of individual piles of trash placed on the side of the road for pickup, with a unit defined as a pile at least one square meter in size, no more than 10 cubic meters in volume, and at least three feet apart from other piles as defined by the city of Tucson. The study found that neighborhoods with a higher median household income produced more trash than those with lower income levels. This could be due to wealthier households having more disposable income that allows them to purchase more items that will eventually be discarded, that wealthier households move homes more frequently and thus need to discard furniture and appliances more frequently, or that wealthier households have more resources to undergo home renovations and therefore discard more bulk waste in the form of furniture, appliances, and building materials. Based on these results, practical applications of the data are discussed as they pertain to improving local waste management policies and strategies for waste reduction. Future studies should examine all 26 waste management districts and the types of waste produced.
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What Can Better Solar Education Do?While Arizona has abundant solar resources, policy decisions, regulatory changes, and the absence of state level incentive programs has limited the states solar adoption rate. This study examines if better solar education can change the way people in Pima County, Arizona purchase, manage, or make decisions about solar energy technologies. With the counties high solar irradiance of almost 300 days of sunshine (80%) a year, solar power has serious potential, but adoption remains limited due to knowledge gaps, economic barriers, and policy challenges. This longitudinal survey was conducted across two semesters of Fall 2024 and Spring 2025, and there were 68 participants in the first survey and 74 participants in the second survey. Results show that better solar education is supported by over half (56%) of the participants surveyed, because they believe better solar education improves solar purchasing/management decisions. The interviews confirm the survey results, with cost savings as the main consumer driver, distrust in some solar companies, and the affordable option of Power Purchasing Agreement’s for people who cannot afford the cost of solar installation. The study further finds that solar education plays an important role in boosting solar adoption, addressing misinformation, and improving policy. The public’s support for solar education, incentives/rebates, and energy conservation programs, says that Pima County could greatly expand its clean energy sector, providing jobs, and clean energy for the future generations of this region.
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Mitigating the Use and Waste of Water in the Construction Sector Regarding StuccoThis Capstone research was conducted to assess the issue of water waste in construction, more specifically how it is involved with the process of stucco; a very popular construction practice that is used here in Arizona and how the water use could be mitigated. Construction is already a process that puts a very heavy use on water due to several factors including requirements from common practices, clean up, and dust control. In the state of Arizona, these factors are somewhat multiplied due to the various materials that are used and the plentitude of dust that requires water to keep settled. With fresh water access and water use already being a worldwide problem, it is imperative that water management becomes one the top priorities. Millions of gallons of water are used everyday in stucco assembly and clean up so it is critical to create and implement methods that help cut back on how much water is used. To spearhead finding a solution, this research used storytelling, first person observations and document analysis. The discussions and conclusions allowed to develop a formula that can help quantify how much water is needed for a given amount of stucco plaster and ideas regarding how this practice can be implemented on all job sites.
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Goshen Food Forest and Community SpaceFood forests are layered ecosystems that improve biodiversity through permaculture techniques, food security, environmental health, and community empowerment. Many food forests have been created throughout the country and world but often are designed based only on what grows native in that region. However, to create a successful food forest for the city, it must meet the needs of the residents. Data was collected from residents of Goshen, Indiana, through surveys, systematic document review, and observational analyses to find the most valuable produce to be included in the food forest design. This data provided context for resident demographics and locations, food growth interest, and preferences for a community space. Case studies of other food forests, reports, and weather data emphasize the value that vegetation has on communities, the importance of local businesses, and how growing conditions can be utilized for successful yield. The study found that many fruits, vegetables, and herbs that Goshen residents prefer can grow in the Northern Indiana climatic region and the community space should prioritize water, seating, and open space. Through utilization of collected data from residents and information from case studies of food forests, a sustainable design for the site can be created. Localism, walkability, and health are priorities for Goshen residents and the implementation of a food forest and community space in the city can provide support for the diverse populations through free and accessible healthy produce.
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Post disaster urban resiliency: a case study of Los Angeles wildfiresWildfires are a growing threat to urban development in California, particularly in Los Angeles where expanding neighborhoods continue to overlap with high-risk fire zones. This study explores whether repeated wildfire disasters motivate urban planners to adopt resilience strategies in real estate development. By combining a literature review with policy analysis and a qualitative interview with a professional in the planning field, the research looks at how planners, developers, and governments respond to post-wildfire challenges. Key themes include the political and structural barriers that prevent long-term resiliency planning. Case studies from Paradise, Santa Rosa, and Boulder demonstrate how some cities implement resilience, while others revert to pre-disaster norms. Findings suggest that although awareness of wildfire risk is increasing, the incorporation of resilient urban planning remains inconsistent due to political influence, limited government authority, and economic pressures. The study shows that improving wildfire recovery takes more than just more resilient building. It also needs support from politicians, the community, and stronger rules.
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Identifying Locations for Wildlife Crossing in Tucson, ArizonaAs the population expands, interactions between humans and wildlife are increasing. In Tucson Arizona, bobcats, mountain lions, coyotes, and javelinas are common visitors, and while not all interactions between humans and animals are negative, negative interactions do happen. There are many ways to decrease wildlife-human interactions and wildlife crossing is one of them. Using a mixed method approach based on case study examination and secondary data analysis, this research aims to identify areas where wildlife crossings in Tucson should be placed. Using data from iNaturalist and the Pima County Open Geodatabase on wildlife sightings, roadkill locations, and tree equity scores, multiple maps were created in ArcGIS Pro to locate areas where wildlife crossings are needed in Tucson. The results showed significant sightings of bobcats, mountain lions, javelinas, and coyotes in Tucson, Arizona. A lot of them are in the upper half of Tucson, closer to current wildlife crossings as well as areas with high tree density. This is important because while there are quite a few wildlife sightings in Tucson, there are no wildlife crossings in Tucson. Some policies that can be added to decrease wildlife-human interaction include a ban on leaving pet food outside or adding a wildlife feeding ordinance that keeps humans from feeding wildlife. Further research can examine why wildlife are attracted to certain areas in Tucson and the potential of creating wildlife crossing in areas with high wildlife sightings and deaths.
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IMPACT OF CLIMATE CHANGE ON WHISKY PRODUCTIONClimate change is altering environmental conditions critical to Scotch whisky production, specifically optimal precipitation and temperatures for barley yields. This study employs geospatial analysis to assess climate patterns and agricultural shifts within whisky-producing regions of Scotland. Climate data from the UK Met Office and agricultural reports from the Scottish Government are used to analyze temperature and precipitation trends impacting barley farming. Statistical modeling determines correlations between climate trends and whisky production factors, with choropleth maps and temporal analysis graphs visualizing the findings. The results provide insights into the vulnerabilities of whisky production and inform adaptation strategies for distilleries. Understanding these environmental impacts is crucial for sustaining the industry amid ongoing climate shifts.
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UNDERSTANDING FATAL CRASHES IN PORTLAND: A SPATIAL ANALYSIS OF SOCIOECONOMIC, BUILT ENVIRONMENT AND VEHICLE SPEED FACTORSThis article presents a case study analyzing the opportunities provided by the Portland open data repository on vehicle speed to explore the relationship between vehicle speed and road safety. While the influence of vehicle speed on road safety has been well-documented on highways and freeways, where free flow conditions are generally uninterrupted by pedestrians or bus stops, this study shifts focus to urban core roads, which include arterials and collector roads. These types of roads account for 69% of road fatalities in the U.S. and are characterized by a higher density of diverse road users, making the interaction between vehicle speed and safety more complex. Using Geographically Weighted Poisson Regression (GWPR), the study examines the associations between vehicle speed and fatal road crashes at the block group level. The goal is to assess the significance of vehicle speed in predicting fatal crashes while identifying spatial variability across the city. This analysis aims to provide insights that could inform localized interventions, particularly in ethnically diverse areas that disproportionately bear the burden of road fatalities.
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Increased Frequency and Potential Environmental Impacts from Oil Spills After Hurricane LandfallsThe increased frequency of oil spills, specifically after hurricanes, can have lingering effects throughout the ecosystem and can cause complexities while restorative efforts are underway. Certain environmentally sensitive areas require different restoration techniques to allow for proper removal of oil with minimal disturbance to the habitat. This project aims to compare oil spills immediately after a hurricane and a non-hurricane event, allowing for a visual representation of increased frequency. Displaying environmentally sensitive areas within the reach of oil spills will illustrate potential impacts of protected and vulnerable land. With numerous sources of publicly available data, we can display where and how much sensitive land may be impacted. Analyzing distance from oil spills, focusing on protected habitats, and concentrating on the most vulnerable and sensitive land will give a precise picture of the lasting impacts of a hurricane. This study looked at two different four-day periods. The first one during normal weather events, and the second was immediately after the landfall of Hurricane Ida. Results show that there was a 600 percent increase in pollution events over a four-day period. This project focuses on one specific hurricane event but provides valuable information. With more time and personnel this process can easily be scaled up to each hurricane that makes landfall in the U.S. Understanding increases in pollution events beforehand, knowing which areas are most vulnerable, and ensuring resources can be deployed easier and faster can allow for less impacts on wildlife and the environment.
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Wildland Fire Risk Analysis on the Fort Apache Indian ReservationWildfires pose a significant threat to natural resources, communities, infrastructure like homes on the Fort Apache Indian Reservation. This project developed a GIS- based wildfire risk assessment model utilizing available data and analytical tools in ArcGIS Pro. The analysis incorporated key environmental variables including fuel models from LANDFIRE, topographic features derived from USGS Earth Explorer, and proximity to communities. A weighted overlay approach was applied to classify areas into no risk. low, moderate, high and extreme wildfire risk zones. By adapting methodologies like kriging and weighted overlay, this study has ensured a replicable and objective assessment and framework. The final wildfire risk maps are able to support land managers in prioritizing mitigation efforts and resource allocation for planning and emergency response efforts.
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A Modelbuilder Workflow for Automating Contour Generation from High-Resolution Elevation Data in a Mosaic DatasetThis project streamlines the topographic-contour generation process for the New Mexico Bureau of Geology and Mineral Resources (NMBGMR). Historically, the NMBGMR generated contours internally to leverage access to high-resolution elevation rasters and maintain control over the level of detail and smoothness. Creating contours from elevation data involves a multi-step workflow requiring manual input, mosaicking, reprojecting, clipping, appending data, field calculations, and generalization. This work develops an automated geoprocessing tool using ModelBuilder in ArcGIS Pro, replacing manual steps with a simplified, repeatable process. The model uses a mosaic dataset to efficiently manage the multiple raster tiles used to generate contours. Integrated into the tool is the optional capability of unit conversion, allowing for the creation of contours in either meters or feet, automated clipping to a designated map extent, contour creation at designated intervals, appending to an existing feature class, and attribute calculations. Testing on map areas with steep, mountainous terrain confirmed that the model accurately replicates the original workflow while reducing complexity. The outcome is a user-friendly tool that standardizes contour creation and improves the efficiency of GIS specialists/cartographers when building map kits used by field geologists. This advancement allows for consistent and rapid production of accurate, map-scale appropriate contours to provide topographic context for the overlying geologic data and supports the production of high-quality cartographic layouts.
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Automated Evacuation Routing with ArcGIS Network AnalystEfficient and adaptive evacuation routing is essential for public safety during disasters such as wildfires, floods, and debris flows. Many traditional evacuation planning methods lack real-time adaptability and fail to account for road closures, congestion levels, and network constraints. This project develops an automated evacuation routing model using ArcGIS Network Analyst, integrating geospatial analysis techniques to generate optimized evacuation routes based on user-defined evacuation zones. A web-based application enables emergency managers to define evacuation zones by drawing a polygon, which triggers the routing model to compute optimal evacuation routes in real time. The model incorporates road closures, restricted access roads, and functional classifications to ensure that only available and suitable roads are used for evacuation. By analyzing residential parcel densities within the evacuation zone, the system assigns congestion penalties to road segments, dynamically influencing optimal route selection. The script automatically identifies exit points at the boundary of the evacuation zones where roads provide safe egress, ensuring logical and efficient evacuation paths. The model was tested using a road network dataset for Santa Barbara County to evaluate its effectiveness in real-world scenarios. This framework is scalable and adaptable, allowing emergency managers to tailor evacuation planning for various disaster scenarios and apply the model to different geographic regions and network datasets. By leveraging network analysis, GIS automation, and interactive web mapping, this project enhances disaster preparedness and response efforts, providing a flexible, real-time evacuation planning tool that supports data-driven decision-making and ensures safer and more efficient evacuations.
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Detached from Détaché: Availability of Orchestra Programs in a Subset of Public Arizona District SchoolsSchool orchestra programs provide instruction in the bowed string instruments (violin, viola, cello, double bass). Along with band and choir, orchestras comprise one of three main music performance ensembles found in schools. Despite orchestra’s importance in a well-rounded music education, orchestra is not as accessible as band or choir because orchestra is typically found in large, suburban, higher-income schools with majority White students. This study aimed to determine the availability of orchestra in a subset of public Arizona district schools, as well as attributes of the schools, such as student demographics and free and reduced-price lunch (FRPL) percentages. Public datasets containing enrollment and FRPL information were joined to an Arizona schools spatial dataset. The AZ School Report Cards website, AZ Arts Education Data Explorer, and individual school and district websites provided orchestra offering information. The schools were spatially joined to public school districts in Arizona, and finally descriptive statistics were calculated. Maps show where school orchestra programs are found as well as lacking, highlighting inequalities in access. In Maricopa County, public school districts in the east and northeast had the highest percentages of schools offering orchestra, with less representation in west and southwest public school districts. In Pima County, public school districts in and around Tucson had high percentages of schools offering orchestra.
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Predicting Areas of Debris Flows in Recently Burned Areas Using Precipitation ForecastsDebris flows are all too common in Southern California, especially in burned areas after a wildfire. This project predicts and informs of potential areas where a debris flow is likely to happen in the 10 counties of Southern California. Using digital elevation model data from the United States Geological Survey (USGS) and water catchment data from the United States Geological Survey’s Elevation Derivatives for National Applications (EDNA) database, the average slope was found in each water catchment, as debris flows follow the flow direction in the catchment. Using the National Interagency Fire Center’s fire perimeter data, recently burned areas were identified, as they are more susceptible to debris flows with the lack of vegetation holding the soil in place. Additionally, the National Weather Service’s National Digital Forecast Database (NDFD) was used to track predicted rainfall accumulation over 72 hours. This live data updates in 6-hour intervals, closely monitoring how much precipitation is expected. A model was created to analyze the data and make predictions on what is considered a no risk, low risk, medium risk, and high-risk area. An ArcGIS Dashboard was created to publicize the data, which provides information about what areas are prone to a debris flow, to help evacuate people and help utility crews with prevention and cleanup measures.
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Developing an Interactive Tool for Identifying Flood-Prone Areas Based on the Topographic Wetness IndexDetermining areas at risk of flooding is critical to minimizing the damage and losses that floods can cause. Geographic Information Systems can map regions of general flood vulnerability through more rapid methods than complex hydrological models. This project aimed to develop an easily operated tool to locate potentially flood-prone landscape areas by applying the Topographic Wetness Index to measure how terrain influences water runoff and accumulation. The result was an interactive Jupyter Notebook that provided detailed steps on using Python code blocks to perform index calculations. Functions of the tool included automating the downloading process for Digital Elevation Models based on user-provided coordinates and performing raster analysis to determine the input parameters of flow directions, accumulated flow, and slope gradients. A set of optional steps could process the index results according to the needs of the user through low-pass filtering, range scaling, and custom symbolization. The project provided an example of how the tool performs by comparing index values from Digital Elevation Models at differing resolutions to descriptions of localized flooding risks in Lake County, Oregon. The Topographic Wetness Index tool effectively demonstrated a practical approach for land use planning purposes that uses minimal inputs to identify areas susceptible to flooding.
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Investigating Trends, Causes, and Patterns of Idaho WildfiresWildfires have become increasingly more common in much of the West, posing a large threat to both human and natural resources. This study uses a variety of spatial statistical methods to investigate the patterns, trends, and causes of wildfires across the state of Idaho. Leveraging tools such as the Global Moran’s I and Hot Spot Analysis to identify significant clusters and emerging trends of fire patterns, Standard Deviational Ellipses were also employed to show the dispersion and orientation of wildfire occurrences. Regression analysis, including ordinary least squares (OLS) and geographically weighted regression (GWR), was used to examine how fire management practices influence the spatial patterns of wildfire incident sizes. The results indicate that human and natural-caused fires exhibit reverse patterns: human-caused fires tend to be smaller but more costly, whereas natural-caused fires tend to be larger but less costly. Unsurprisingly, human fires tend to be concentrated around higher population densities, while natural fires tend to occur in more remote areas. These findings highlight the importance of more localized and data-driven approaches to wildfire management and policy decision-making.
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REDLINING AND EDUCATION: INVESTIGATING THE LONG-LASTING IMPACT OF HISTORICAL HOUSING POLICIES IN HENNEPIN COUNTYThe U.S. government created the Home Owners' Loan Corporation (HOLC) as part of the New Deal under President Franklin D. Roosevelt. HOLC refinanced home mortgages to prevent foreclosures and stabilize the housing market. However, its practices, particularly redlining, had long-lasting negative effects on many minority communities. HOLC's grading system, which relied on discriminatory criteria based on racial composition and economic status, marginalized communities of color. The legacy of these practices continues to shape socioeconomic conditions today, as redlined neighborhoods still struggle with lower property values, limited access to resources, and persistent disparities in education, wealth, and healthcare. These enduring effects underscore the long-term consequences of institutional discrimination, which continue to impact affected communities across generations. This study examines the lasting effects of redlining on educational attainment in Hennepin County, part of the Twin Cities in Minnesota, by analyzing decennial census and American Community Survey data. The analysis focuses on key factors at the census tract level, including socioeconomic variables such as housing, employment, and income; demographic factors like race and disability; and access to resources, including technology and transportation. Using regression models, the study identifies significant relationships between these variables and low educational attainment. The results reveal that both low educational attainment and the associated variables vary spatially across Hennepin County.
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Geospatial Interpretation of MARSIS Data: A GIS Approach to Martian Subsurface AnalysisSubsurface water on Mars is key to understanding its geological evolution, climate history, and potential habitability. This study examines 1.5 billion radar signals from the Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS), a low-frequency radar sounder aboard the European Space Agency’s Mars Express orbiter, focusing on the strongest 5% of signals to detect subsurface structures. All 1.5 billion points were evaluated using clustering and statistical methods to detect large subsurface structures up to five kilometers deep, with more than 424 million points forming significant clusters. Using advanced signal processing (e.g., clutter suppression, noise filtering) and geospatial analyses (e.g., spatial clustering, autocorrelation, hotspot analysis, and cross-partition connectivity), the study identifies significant subsurface structures. The findings are validated by NASA’s Shallow Radar (SHARAD) data confirming known shallow ice deposits in mid-latitude regions like Utopia Planitia. Integrated into a GIS framework, these visualizations advance planetary science, astrobiology, astrogeology, and Mars exploration by enabling in-situ resource utilization (ISRU) and informing landing site selection. This study pioneers a GIS-based approach to globally map Martian subsurface water, integrating MARSIS and SHARAD data.