• Open Source GIS Tools for Housing Activists and Advocates

  Korgaonkar, Yoganand; Bessick, Benjamin (The University of Arizona., 2024)

  The U.S. Department of Housing and Urban Development estimates that over 650,000 people were unhoused in 2023. The U.S. has an affordable housing crisis, and advocates and activists across the country are struggling to fix the causes and catalysts for this issue. Prevention, preferable to correction, highlights the importance of keeping people housed as the most desirable intervention. The difficulty with being proactive is in achieving the ability to see the when and where of potential problems before they arise. Geographic Information Systems (GIS) allow problems that are firmly spatially bound, such these, to be investigated in various ways. These systems, however, need training and expertise to be utilized successfully. This project aims to demonstrate a methodology for connecting the spatial and GIS tool expertise of GIST professionals with contextual knowledge and the capacity to operationalize information of advocates and activists on the ground by using a well-established and highly-developed model and toolset for distributed development and collaboration found in the field of open-source software development.
• Optimizing Transformer Management: GIS Analysis and ESRI Tools Field Deployment

  Korgaonkar, Yoga; Mitchell, Matthew (The University of Arizona., 2024)

  The COVID-19 pandemic disrupted supply chains, causing transformer costs to rise two to five times when compared to the 2019 cost, and extending lead times from a few months to over eighteen months. To address this, the Navajo Tribal Utility Authority (NTUA) aimed to locate idle transformers, referred to as "hanging inventory," for reuse. However, NTUA lacked an efficient system for tracking these transformers and relied on employee reports from field visits. To improve this process, I developed a Python-based GIS analysis using existing transformers, powerline, and meter point data to map the relationships between transformers and downline meters. By cross-referencing active meter locations, I identified over 2,000 potential idle transformers. We deployed over 100 tablets equipped with ESRI field software to assist field workers in accurately capturing and updating transformer locations. The project enabled significant data cleanup, uncovering mislocated meters and errors between the automated metering infrastructure system and the GIS database. These findings have enhanced NTUA's asset management by identifying unused transformers, improving resource allocation, and streamlining future maintenance efforts. As a result, NTUA can now effectively manage transformers, helping to mitigate ongoing supply chain challenges.
• DEVELOPING PUBLIC TRANSPORTATION ROUTES FOR RURAL CATTARAUGUS COUNTY, NEW YORK

  Korgaonkar, Yoga; Lange, Aimee (The University of Arizona., 2024)

  This study uses demographic data from the United States Census Bureau and Geographic Information Systems tools and methodologies to identify bus stops and routes for a public transportation plan for Cattaraugus County, New York. Located in rural Western New York, Cattaraugus County has an aging population and an average poverty rate of 14%, the fourth highest in the state overall and the highest for rural counties. With only two small urban areas located along the county’s Southern border, most of the county lacks easy access to essential services. Population, poverty, senior citizen, and housing demographic data from the U.S. Census Bureau’s 2020 decennial census and the American Community Survey 2022 5-year estimate data at the census block, group, and tract levels were used to identify the best bus stop locations. ArcGIS Pro and Suitability analysis are used to rank and score census data at the block level based on weighted criteria to determine the best area/location for a bus stop. Utilizing the bus stop locations, bus routes are identified using Network Analysis while considering winter driving conditions, rural road conditions, distances, and time. Secondary bus stops within a mile and a half of the direct route are identified to allow for deviated routes, where passengers can call in before a pre-determined time and request a pick-up. Carefully thought-out bus stops and routes place public transportation where they are needed most and will be utilized.
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  COMPARATIVE ANALYSIS OF PRECIPITATION AND POPULATION DATA IN ARIZONA USING ARCGIS PRO AND QGIS

  Korgaonkar, Yoga; Horvat, Autumn (The University of Arizona., 2024)

  This project assesses the efficacy of ArcGIS Pro and QGIS for conducting geospatial analysis utilizing precipitation, temperature, and census data across Arizona. The primary data sources are annual precipitation data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) and U.S. Census population data from the United States Census Bureau from 2010 to 2020. Temperature and precipitation data were analyzed in both ArcGIS Pro and QGIS to showcase rainfall and temperature disbursement across Arizona’s census tracts. Population density was calculated and normalized in each platform to evaluate each platform’s capability and usability. Both platform’s geoprocessing tools uncover spatial trends throughout the state. A series of tables and maps were created to display these results. The results highlight the strengths and shortcomings of ArcGIS Pro and QGIS in managing large datasets containing demographic and environmental data. This project offers insight into ArcGIS Pro and QGIS proficiency for similar geospatial analyses.
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  Children’s Equity Nature Index (CENI): An Analysis of Young Children’s Equitable Access to Public Green Spaces in Urban Pima County, Arizona

  Korgaonkar, Yoga; Hammond, Ellie (The University of Arizona., 2024)

  Studies have demonstrated that access to safe public green spaces and other protective community resources is crucial for childhood development between the ages of 0 and 4. By providing every child with the chance to form a meaningful connection with nature, communities can work to ensure a bright and resilient future for their youth. For equitable nature access to be achieved, several factors must be considered that impact the relationship between young children and public parks, including socially vulnerable demographics, proximity to parks, transportation networks, park quality, and public safety. The Children’s Equity Nature Index (CENI) is a composite index designed to map these relationships within the metropolitan areas of Pima County, Arizona. The CENI is made up of two main sub-indices: the Equity Priority Sub-Index, which considers demographics specific to the region that face a higher degree of vulnerability, and the Children & Nature Sub-Index, which examines green space quality, transportation access to green spaces, and the population density of children 0-4 years old throughout the study area. The final map shows the urban census block groups within Pima County that contain more children living in areas with higher social vulnerability and lower access to quality green spaces, which the CENI identified as predominantly highly developed block groups within Tucson’s city limits. With this information, community investment through funding, programs, partnerships, and policies can be designed specifically for the areas within the study area that need them the most.
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  Filters Cannot Correct all Flaws

  Korgaonkar, Yoga; Rowland, Dana (The University of Arizona., 2024)

  A severe concern of contamination from Per- and Polyfluoroalkyl Substances (PFAS) surfaced in May of 2017. The local water sources of Airway Heights, Washington showed to have PFAS compounds that were uncommon. The state’s small city sits east of Fairchild Air Force Base (AFB). In 1993 Fairchild AFB was put on the National Priorities List (NPL) for water contamination in conjunction with an underground leak of JP-4 fuel. Similarly to water testing twenty-four years prior, Fairchild AFB underwent well testing on base and off-base in the Spring of 2017. The goal of this project was to assess research data, primary sources, current clean-up plans and findings to contextualize if the claims that the water contamination was solely due to Fairchild AFB's firefighters' aqueous film-forming foam (AFFF) finding its way into the potable water sources of Airway Heights, WA stands resolute today. Could it be possible that one or multiple sources of PFAS compounds are to bear some responsibility? Areas of interest were wildland fires, landfills, and historical locations of aircraft crashes within the boundaries an area deemed ‘West Plains’ in Spokane County, Washington, and the possibility that pesticides utilized on local farmlands could have contained hazardous PFAS compounds. Methods used to compile empirical data were first-hand conversations with subject matter experts (SME) and department leads of WA environmental agencies, primary source reports, peer reviewed articles, and media articles. Current results show possibilities lying with historical usage of AFFF from historical events of the area and a local landfill that was used for all wastes, including hazardous waste.
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  ANALYZING FEMA’S COMMUNICATIONS LIFELINES SUBCOMPONENT OF ELECTRONIC PAYMENT PROCESSING TO DETERMINE EFFECTS ON THE COMMERCIAL FOOD DISTRIBUTION SUBCOMPONENT DURING STAFFORD ACT DISASTERS

  Korgaonkar, Yoga; Green, Josh (The University of Arizona., 2024)

  During Stafford Act events, which authorize the President to issue declarations for federal assistance in response to incidents, rapid decision-making using the best available data is crucial. In the ESF #2 (Communications), Emergency Managers rely on VISA’s data to determine the availability of electronic payment processing and assess disruptions related to grocery stores providing food to survivors (Commercial Food Distribution Subcomponent). This project aims to create a template that transforms daily data, received every morning at 10:00 AM, into actionable information. The problem at hand is the need for faster data analysis to generate timely information about disruptions to a lifeline (A lifeline enables the continuous operation of critical government and business functions and is essential to human health and safety or economic security). Currently, manual data analysis is time-consuming and diverts resources from other critical tasks. To address this, we will use ARCGIS and PyCharm to plan to set up the supporting data and Service Area tools to understand the grocery stores available within a 15-minute drive time. Then, we will utilize the Tabulate Intersection (Analysis) tool to determine the population served by grocery stores before and after an incident. This approach reveals one primary result: it assesses the extent of disruption to the electronic payment processes and Commercial Food Distribution lifeline subcomponents using the supplied data. This project aims to improve the efficiency and accuracy of our response during critical events, ensuring better resource allocation and support for affected populations.
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  Searching for AA Deserts - A Case Study of Tucson, AZ in 2023 to Improve Meeting Area Coverage

  Lukinbeal, Chris; Soto, Rebecca (The University of Arizona., 2024)

  The aim of this study is to examine the location and frequency of Alcoholics Anonymous meetings within the greater Tucson area and determine where best to position new meetings. AA has a large impact on the well-being of those who are in sobriety – it is a form of fellowship that cannot be found in many other places. To accomplish this, meetings recorded for fall of 2023 will be examined, and a time series analysis will be done by looking at day of week and time of day, followed by a suitability analysis to determine how close new meetings should be to those already established. These analyses may also help in determining a network analysis for those who wish to travel to established meetings, as well as seeing if there are areas considered an ‘AA desert’, similar in concept to a food desert (areas that are lacking in resources to accommodate for food deficiencies or AA meetings). In doing several of these analyses, it is apparent that there is a greater need for meetings outside of working hours, e.g. early morning and late night, as well as a need for more outside of city limits but within metro areas.
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  RARE PLANT CONSERVATION: A GIS-BASED APPROACH TO ASSESSING SUITABLE HABITAT WITHIN THE CALIFORNIA STATE PARKS, SANTA CRUZ DISTRICT

  Marcus, Matthew; Williams, Vaughan (The University of Arizona., 2024)

  Conservation practitioners face complex decisions when considering species conservation planning, particularly with rare species and landscape-level habitat management. The California State Parks, Santa Cruz District manages 72,290 acres within 44 parks in Santa Cruz and San Mateo Counties. Rare plant species pose specific conservation challenges in these areas, and a broad and comprehensive baseline approach to their conservation has not been conducted. This study focused on five rare species: San Francisco collinsia (Collinsia multicolor), Mash microseris (Microseris paludosa), San Francisco popcorn flower (Plagiobothrys diffusus), Santa Cruz microseris (Stebbinsoseris decipiens), and Pacific grove clover (Trifolium polyodon). Using the habitat suitability modeling tool in ArcGIS Pro, I developed five unique habitat suitability models tailored to each species ecological niche. These models integrated criteria including digital elevation models, detailed vegetation data, soil descriptions, and known population distributions. Within each criteria, categories were ranked using a suitability score from 1 (low) to 10 (high). Suitability scores from each criteria were then added, resulting in a final suitability score. These scores were then exported to a raster and symbolized based on those high to low suitability scores. Preliminary findings provide general insights for California State Parks staff, particularly when assessing wide scale management techniques. These models offer predictions of unknown populations within Parks sites and identify suitable habitat for targeted restoration efforts. Each species model predicted suitable habitat within State Parks boundaries, including areas without current occurrence records. Known occurrence records were used to adjust each model to reflect optimal habitat for current populations. This research underscores the importance of integrating advanced spatial analysis techniques with field data to support conservation and biodiversity management practices. Finally, these findings can inform broader conservation goals and guide future management practices within the Santa Cruz District of California State Parks system and beyond.
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  EVALUATION OF FINE PARTICULATE MATTER AIR SENSOR DATA AND INTERPOLATION MODELS IN PHOENIX, ARIZONA

  Marcus, Matthew; Toon, Elias (The University of Arizona., 2024)

  Chronic and acute exposure to fine particulate matter in ambient air has increasingly been linked through epidemiological studies to negative health outcomes. The rise in popularity of low-cost air sensors presents an opportunity to potentially improve interpolation predictions for fine particulate matter by combining air quality monitor data with air sensor data. However, the use of air sensor data presents data quality concerns when compared to air monitor data which must conform to federal methods. Recently, U.S. EPA researchers have developed a correction equation to reduce bias in PurpleAir sensor measurements. This study aims to evaluate the potential for using public PurpleAir sensor data and interpolation models to generate fine particulate matter concentration prediction surfaces for Phoenix, Arizona. This study uses geostatistical analyses to evaluate interpolation model performance using three datasets: 1. air monitors, 2. air monitors and uncorrected air sensors, and 3. air monitors and corrected air sensors. This study also evaluates interpolation performance by ranking cross-validation statistic scores for model bias, prediction accuracy, precision, worst-case error, and standard error accuracy for each data scenario. Models for data processing, cross-validation, and interpolation automation will be made available for the purpose of reproducing these analyses in other locations. Based on fine particulate matter concentration data collected from the study area between December 17 - December 31, 2022, the ordinary kriging optimized interpolation technique achieved the highest average rank with the “air monitors” and “air monitors and corrected air sensors” data scenarios achieving an equal weighted average rank.
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  THE FUTURE OF THE SOUTHWEST LIGHT RAIL TRANSIT PROJECT: PREDICTING CRIME WITH SPATIAL ANALYSIS

  Lukinbeal, Chris; Whetstone, Lauren J. (The University of Arizona., 2024)

  Metro Transit is the main public transportation network in Minneapolis and St. Paul. The transportation network is comprised of light rail, buses, and commuter trains. The light rail network is comprised of two lines: the METRO Green Line and METRO Blue Line. The Southwest Light Rail Transit project is going to extend the METRO Green Line 14.5 miles to connect downtown St. Paul to downtown Minneapolis and surrounding locations. Residents have voiced concerns that the extension will bring crime to their neighborhoods because there is a perception that there is a higher amount of crime near light rail stations and platforms. The study examines crimes in Minneapolis and St. Paul from the years 2019 through 2023. Geographic Information System (GIS) analysis is utilized to produce a kernel density map of total crimes throughout each city. Visually, the kernel density map shows that there are crime hotspots in downtown St. Paul and downtown Minneapolis. A buffer analysis was also conducted by creating a buffer around each light rail station or stop along both Blue and Green Lines to calculate the number of crimes per 0.25 mile. The stations with the highest crimes per 0.25 mile were all located in downtown St. Paul and Minneapolis. Population density for each neighborhood was used to help determine the rate of future crime at the five new stations in Minneapolis. Light rail stations and stops are found to have higher crime at their downtown locations compared to other locations in the cities.
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  RELOCATING FOR RETIREMENT: A 2024 SITE SUITABILITY ANALYSIS FOR FINDING THE IDEAL RETIREMENT LOCATION IN WESTERN WASHINGTON

  Lukinbeal, Chris; Mast, Michael (The University of Arizona., 2024)

  Each year, millions of Americans retire from their jobs. Although there are numerous retirement planning resources focused on financial preparation, very few focus on the other aspects of retirement. Left without the sense of purpose, social interaction, or structured routines of the workplace, many retirees can find themselves bored, lonely, and depressed. Considering a person’s mental health is unique to them alone, the requirements that make up their idea of a healthy retirement is also unique to them. Once those needs are understood, GIS tools can be used to create a process model to highlight potential retirement locations. This study, limited to western portion of Washington state for simplicity, focuses on the needs of a retiring military member, comparing their housing, schooling, and lifestyle requirements through a combination of Boolean and weighted analyses to determine potential areas for retirement. In choosing a location identified by the model, it would be expected that the retiree’s needs would be met, leading them to lower stress, a greater mental wellbeing, and a more successful retirement.
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  MONITORING DROUGHT RESISTANCE OF CORN, SOYBEANS, AND OATS IN IOWA FROM 2000-2023 USING REMOTE SENSING

  Lukinbeal, Chris; Cunningham, Jimmy (The University of Arizona., 2024)

  Since 2000, Iowa has had over $10 billion in crop loss insurance payouts, in which droughts were the largest weather-related factor. The aim of this research is to use remote sensing to demonstrate how much more drought resistant corn, soybeans, and oats have become. The three crops being observed are corn, soybeans, and oats from 2000-2023 between May 15th and October 15th, which is considered Iowa’s growing season. Currently both genetic modification, in corn and soybeans, and non-genetic modification, in oats, are being used to increase these crops’ ability to resist drought. The U.S. Drought Monitor labels areas of drought and classifies them by intensity using many different factors, with some being precipitation, soil moisture, vegetation health, etc. From this, an average drought intensity number for each year’s growing season is calculated. Using remote sensing data from the Landsat 5, 7, and 8 satellites, an index is calculated showing how drought affected vegetation is. CropScape is a tool maintained by George Mason University that shows crop-specific land cover, this is used to separate and display each crop with the previously mentioned index. Each year’s crop yield totals (in bushels/acre), from the National Agricultural Statistics Service, are presented to see if they correlate with recorded and calculated drought conditions. Using these methods and indices, it is shown that drought conditions are having less of an effect on crops in Iowa over time, meaning that corn, soybeans, and to a lesser degree oats, have become more drought resistant.
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  BUILDING ARCGIS DASHBOARDS FOR POWER DATA PROGRESS MONITORING FOR SPANISH FORK CITY, UTAH

  Lukinbeal, Chris; Woodhouse, Wesley (The University of Arizona., 2024)

  For an Outage Management System to be fully functional, an electric utility company must accurately digitize its data within a Geographic Information System. Spanish Fork City, Utah began migrating and digitizing their Power and Light data within the ArcGIS Utility Network, which has proven to be an expensive and time-consuming process. In order to justify the expensive nature and continued funding of this project, city management and administration need a way to visualize and understand the current state of the city’s power data. Many organizations use dashboards as a comprehensive overview to monitor, analyze, and disseminate information for projects and visualize real-time progress. This paper describes the process I used to create such dashboards for management and administration to utilize. In this project, I created various attribute rules in ArcGIS Arcade to accurately aggregate data from multiple geodatabases across an ArcGIS Enterprise environment, which automatically populates numerous fields within a custom grid feature class. I published services in ArcGIS Pro, which are utilized in web maps and Dashboards within ArcGIS Portal. I created custom Data Expressions in ArcGIS Dashboards to allow specific indicators to work correctly. Each set of indicators and widgets are interactive with their respective maps, allowing users to focus on specific areas.
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  The Impact of Social Determinants of Health on Cancer Screening Rates in the Contiguous United States

  Lukinbeal, Chris; Tillotson, Loyal (The University of Arizona., 2024)

  Although cancer remains the second leading cause of death in the United States, increased screening over the past few decades has played a significant role in lowering cancer mortality. However, Social Determinants of Health (SDOH), which encompass the non-medical factors influencing health outcomes, show that preventative measures such as screening are not universally accessible and utilized. The purpose of this study was to identify which SDOH variables had the greatest influence on colon, cervical, and breast cancer screening rates and see how variable influence changes geographically across the contiguous United States. The two primary tract-level datasets used for this analysis were the 2011-2015 U.S. Census Bureau’s American Community Survey (ACS) 5-year estimates and the 2022 model-based Population Level Analysis and Community Estimates (PLACES) from the Center for Disease Control. Exploratory and Geographically Weighted Regression was conducted in 2024 using ArcGIS Pro Desktop 3.1.2, generating models that helped explain why the rate of cancer screening varies widely across the lower 48 states, even within small regions. Certain variables that correlated with cancer screening rates included health insurance coverage, routine physician checkups, English-speaking households, household size, and home internet access. Overall, these variables show that poverty is indeed a strong determining factor in whether adults in the U.S. will get screened for cancer.
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  SPATIAL ANALYSIS OF RESIDENTIAL LOCATIONS FOR MILITARY PERSONNEL IN SAN ANTONIO, TEXAS

  Lukinbeal, Chris; Nichols, Erin (The University of Arizona., 2024)

  Finding the ideal residential locations is crucial for enhancing quality of life and efficient urban planning. This study, conducted in 2024, focuses on San Antonio, a city with diverse neighborhoods and unique geographical features, with a particular emphasis on the needs of military personnel and their families. The project aims to identify the best residential locations by evaluating the average distances to essential services, specifically the Fort Sam Houston area, using Geographic Information Systems (GIS). Spatial data was collected and analyzed using GIS technology to assess proximity to essential services, including schools, grocery stores, police stations, fire departments, and military bases. Based on these criteria, various spatial analysis techniques were employed to determine the optimal residential areas for the military demographic. The analysis identified several key areas in San Antonio that offer proximity to essential services, making them ideal for military personnel and their families. These findings highlight the spatial patterns and accessibility of services across different neighborhoods. The results provide valuable insights for potential military residents seeking convenient and accessible living areas, as well as for urban planners aiming to improve infrastructure and service distribution in San Antonio. The study underscores the importance of GIS in urban planning and residential decision-making.
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  ENHANCING HURRICANE PREPAREDNESS AND RECOVERY: A COMPREHENSIVE ARCGIS HUB FOR THE CITY OF DAPHNE, ALABAMA

  Bond, Kathryn (The University of Arizona., 2024)

  Personal readiness for emergencies plays a vital role in minimizing the adverse effects of disasters. Hurricanes pose significant threats to communities, and inadequate preparedness can lead to devastating consequences for individuals. Addressing barriers such as insufficient emphasis on disaster preparedness, lack of information, and lack of motivation is essential for enhancing community resilience and ensuring citizen safety. This project seeks to address the problem of inadequate hurricane preparedness in the City of Daphne, Alabama. Many citizens are unprepared due to challenges in accessing and understanding essential information for hurricane preparation and response. To tackle this issue, this project will create a comprehensive ArcGIS hub site and dashboard to centralize information on hurricane preparation and recovery. The hub site will serve as a primary landing zone, while the dashboard will provide specific guidance on hurricane preparation. Data sources, including Active Hurricanes, Cyclones and Typhoons from the National Hurricane Center, city layers for road closures, and county layers for emergency shelters and hurricane preparedness will be integrated to ensure comprehensive coverage of essential information. Citizens will be able to locate current road closures, find the closest shelter, observe active storms, and locate important preparation material, which will help them prepare effectively, make informed decisions and resume normal activities more quickly after a hurricane event. By improving access to crucial information and guidance, the project will contribute to a safer and more resilient community.
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  Temporal Trends of Robberies in Brooklyn, New York 2023

  Lukinbeal, Chris; Mustafa, Haley (The University of Arizona., 2024)

  Robberies are believed to be influenced by temporal trends such as time of day, day of the week, and season. To test this claim, a spatial regression analysis was performed on robberies in Brooklyn, New York for the year 2023. In 2023 a total of 4,316 robberies occurred. However, each of these robberies were sorted into the three temporal trends listed above. Time of day was sorted into morning, afternoon, or night. Day of the week was sorted into weekdays or weekends. Seasons were sorted into winter, spring, fall, and summer. After, the robbery dataset was spatially joined into the Brooklyn census tracts to run the spatial analysis. For each temporal category a local bivariate relationship model was run to determine the type of relationship between the robberies and temporal trends. An exploratory regression was also run to get the adjusted R- square values and corrected Akaike’s information criterion (AICc). After the models were run, the top neighborhoods with the highest number of robberies for each trend were reported. It was found that night robberies had the highest positive relationships in the time-of-day trend. Weekdays were found to have the highest positive relationship between time and robberies in both the day of the week trend and all other temporal trends. Spring had the highest positive relationships in the season trend. The neighborhood that had the most robberies in multiple trends was East New York. These models support the claim that robberies are influenced by temporal trends.
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  FROM 2017-2021, WERE THERE FEWER PEOPLE AT RISK OF HIV ADVANCEMENT IN METRO ATLANTA, GEORGIA?

  Lukinbeal, Chris; Kemp, Lena (The University of Arizona., 2024)

  The human immunodeficiency virus (HIV) is an incurable pandemic that is more common than most people may think. In the United States alone, many of the southern states have the highest percentage of new HIV diagnoses. Because of this, this project specifically analyzes Metro Atlanta, Georgia, comprising five counties: Cobb, Fulton, Gwinnett, Clayton, and DeKalb. This region makes up some of the highest HIV diagnoses in the country. Using 2017-2021 zip codes, I created a dashboard comparing the percentage of residents who received treatment for HIV and those who were still at risk of HIV advancing to late-stage HIV, acquired immunodeficiency syndrome. Unfortunately, the cases-to-risk ratio was meager in this timeframe: Approximately only 27.7% received treatment (cases) whereas by the end of 2021, approximately 72.3% were still at risk (risks). So, to provide Metro Atlanta residents with a resource for HIV testing and treatment, I digitized 109 HIV facility points and created a Web Map displaying local HIV facilities based on HIV testing and/or treatment with addresses, points of contact, and web pages for the public to access facilities closest to their residents. This project is to demonstrate how valuable geographic information systems is in the health industry and to raise HIV awareness. No matter a person’s social, economic, or demographical status, no one is immune to contracting HIV, and all sexually active persons or illegal drug users should get tested either annually, when having a new contact partner, or after using unsterilized needles.
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  LEAST COST PATH ANALYSIS OF THE O’ODHAM ORIOLE SONG SERIES JOURNEY

  Korgaonkar, Yoga; Todd, Mary Elizabeth (The University of Arizona., 2024)

  The Oriole Song Series is a collection of traditional Akimel O’Odham songs that describe a journey from the middle Gila River in southern Arizona to the salt flats on the northern coast of the Gulf of California and back. O’Odham men traveled from their traditional homelands to gather salt, and more importantly, complete a sacred pilgrimage. Anthropologist Donald Bahr recorded Vincent Joseph, a Gila River Indian Community member, recite and sing The Oriole Song Series in the early 1980s, which reference physical locations along a metaphorical route intertwined with O’Odham mythologies. Although visible trail segments, trail markers, and linear artifact scatters exist in the archaeological record, the precise path(s) of the physical journey remains unknown. This study explores the potential physical route(s) utilized by Akimel O’Odham and Peeposh peoples and their ancestors as compared to the metaphorical journey described in The Oriole Song Series. A least cost path was calculated for the entire metaphorical route and the results were compared to trails and trail-related features documented in the archaeological and ethnographic records, historic maps, and modern O’Odham knowledge. Results indicate that the least cost path aligned with the location of documented trails in some segments but diverted away from others. Areas where the least cost path overlaps documented trails suggests these segments were commonly used trails for routine activities, as they were the most expedient route. However, because the least cost path does not come near documented trails in most segments, the songs also demonstrate Akimel O’Odham cognitive mapping of the landscape.

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