Now showing items 21-40 of 206

    • HABITAT SUITABILITY ANALYSIS OF IXODES SCAPULARIS IN THE STATE OF MICHIGAN TO DETERMINE LYME DISEASE RISK

      Mason, Jennifer; McGuckin, Jenny (The University of Arizona., 2025)
      Lyme disease is the most common vector-borne disease in the United States. The disease is caused by the bacteria Borrelia burgdorferi and is largely spread by the black-legged tick, Ixodes scapularis. The black-legged tick, also known as the deer tick, is most common in the Northeast, mid-Atlantic, and upper Midwest. A weighted habitat suitability analysis submodel based on environmental factors was conducted to determine locations in the state of Michigan where deer ticks may exist or could become established if introduced. The results from this submodel were then used as part of a second weighted suitability analysis which also incorporated certain human activities that increase the likelihood of encountering deer ticks. A risk map was generated from the second suitability analysis to display areas that are both highly suitable for tick survival and human activity. The risk map showed a majority of the upper peninsula and northern lower peninsula, along with the west coast and portions of the southeast region, posing a risk to humans should a tick population become established if not established currently. Further studies should be conducted that incorporate tick surveillance programs, Lyme disease incidence rates, and human behavior in and around these higher risk areas to limit the spread of future tick populations and bring awareness to Michigan residents.
    • Comparison of Property Values of Contaminated and Non-Contaminated Sites By Land Use Category in Ramsey County, Minnesota

      Korgoankar, Yoganand; Maas, Geoffrey (The University of Arizona., 2025)
      The commercial and industrial use of land for various kinds of economic activity can result in contamination. Contaminated properties, when not correctly remediated, may persist for years within a community remaining underutilized or unused entirely. Contaminated and underutilized land is a concern to citizens and governments as these properties remove productive land from development and may pose health risks as can contribute to reducing property values for the surrounding properties and can diminish the property tax base used to fund government programs and activities. This analysis will attempt to use geospatial techniques to assemble various types of public data to determine if land values of properties known to contain a contamination record are comparable to land values with sites not having a known contamination record. Land values—normalized by parcel to the unit of ‘assessed value per acre’—of contaminated and non-contaminated sites are compared within their respective generalized land use categories. The study area will encompass Ramsey County, Minnesota (170 square miles). The data for this analysis includes the sites (as point data) of the known contamination from the Minnesota Pollution Control Agency, property values from County records contained in parcel polygon data and existing land use types to be assembled from municipal governments, available as polygons.
    • Automating LiDAR Dataset Retrieval and Geodesic Viewshed Generation with Python

      Mason, Jennifer; Brouse, Jonathan (The University of Arizona., 2025)
      Data collection is often the most time-consuming part of a GIS research project. For a viewshed analysis this involves identifying the coverage areas and selecting the exact grid squares required by the study area. The goal of this tool is to save the end-user time by automating the LiDAR download and viewshed calculation. This tool is run via the ArcGIS Pro geoprocessing GUI through a custom python tool in a custom toolbox. This tool is specifically designed to retrieve LiDAR data from Pennsylvania Lidar Navigator hosted by Pennsylvania Spatial Data Access, or PASDA. The tool generates a polygon around the target site which is used to select LAS grid squares that were imported via REST URL. These LAS grid squares are then used to download their linked LAS datasets, merged into one universal LAS dataset, and then used to run a geodesic viewshed. The completion of this script produces a viewshed layer with automatic symbolization of green: land visible up to eighty feet above ground level, blue: land visible from eighty feet to one hundred twenty feet above ground level, and no fill color for anything above one hundred twenty feet above ground level. Testing with this tool has resulted in successful viewshed calculations with distances between observer and target features ranging from three statute miles to twenty-six statute miles. With the tool successfully downloading and generating viewsheds this tool allows end-users to multitask while this tool runs in the background, effectively saving the end-user time.
    • Conveniently Located Convenience Stores or Inconvenient Konbini

      Mason, Jennifer; Belnap, Michael (The University of Arizona., 2025)
      7-Eleven is the largest convenience store company or brand in the world with over 85,000 locations. Over half of these are in Japan where the parent company of 7-Eleven, Seven & i Holdings, is headquartered out of. Competition for convenience store, or “konbini” in Japanese, dominance comes from other companies in Japan, namely Familymart and Lawson. Okinawa, Japan is no exception to having its share of konbini, but 7-Eleven locations on the island are limited when compared to other major competitors. This project investigates the spatial relationship between 7-Eleven locations in Okinawa and census data for the expansion of 7-Eleven stores. The locations for 7-Eleven konbini were collected from Google while the census statistics and shapefiles were collected from the Statistics Bureau of Japan for 2020. The demographics used from the census data included persons by occupation, construction type, family type, ownership status, household size, economic structure, and age. Ordinary Least Squares regression techniques used within the analysis determine the relationship between convenience store locations and demographics. 7-Elevens have a positive relationship between census tracts containing apartments 11 floors or more, construction types classified as other, household sizes of 1, and women ages 35 – 39, while having a negative relationship with transportation or postal workers. A properly specified model for 7-Eleven locations was not determined due to weak Adjusted R-Squares values and severe multicollinearity present within the census statistics.
    • Modeling the Geographic Distribution of Cantharellus formosus Under Climate Change

      Mason, Jennifer; Zalesky, Travis (The University of Arizona., 2025)
      Maximum entropy, presence-only, species distribution modeling of the current and future habitat of Cantharellus formosus across North America is modeled under a range of climate change scenarios. C. formosus is a culturally and economically important ectomycorrhizal Basidiomycetes mushroom species which is highly prized by foragers for its gourmet flavor. It is symbiotic with Pseudotsuga menziesii (Douglas Fir) and widespread along the US west coast, particularly in heavily forested areas of Washington and Oregon, west of the Cascades. C. formosus has been observed as far south as Berkeley, California, and as far north as southern Alaska, as well as in limited areas of the northern Rockies, near the Canada - Idaho border. Using 663 research-grade, crowed-sourced presence observations obtained from the Global Biodiversity Information Facility and 23 ecological variables, the ecological-niche and species distribution of C. formosus was modeled using a maximum entropy, machine learning algorithm. Further, the future distribution of C. formosus was forecast using a range of climate projections, out to the year 2100. Projections indicate that highly suitable habitat is likely to decline, by 8% to 94%, particularly in California where multiple projections show a complete loss of highly suitable habitat. Conversely, suitable and somewhat suitable habitat may increase by upwards of 100%, as the projected habitat migrates to the north. Importantly, due to the ecology and symbiotic nature of C. formosus, while loss of habitat may occur relatively quickly under changing climatic conditions, establishment and/or expansion into new habitat is likely to be slower by comparison.  
    • BUILDING A WEB GIS APPLICATION FOR LOCATING PARKS AND AMENITIES IN ROSEVILLE, CALIFORNIA

      Mason, Jennifer; Ward, Jennifer (The University of Arizona., 2025)
      Parks are an important part of the community. They provide a place for the public to gather for events, play sports, enjoy the outdoors, and catch up with neighbors. Roseville, California, is a growing city that is continually developing new parks, which can make it difficult for the public to be aware of all the parks and amenities the city has to offer. City parks are often an underutilized public resource. Lack of park awareness is one of the main reasons cited for not utilizing city parks. In Roseville, the public may visit the city’s Parks and Places webpage to view a map of city parks. To find particular park amenities, the public may visit 88 individual park webpages to view each of the static lists of available park amenities for each park. Through this project, an interactive web application is built to eliminate the time-consuming process when searching for park amenities and to provide awareness of the parks and park amenities offered throughout the city of Roseville. ArcGIS Pro, ArcGIS Online, and ArcGIS Experience Builder are used to build an application that allows the user to search for parks by name, map location, or by a desired combination of park amenities. This application will serve as a prototype web application that will allow the public to search Roseville parks and park amenities in a user-friendly way, bringing awareness to all parks and park amenities offered in Roseville.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.