• Tackling Tree Equity: Social and Economic Predictors of Urban Tree Canopy in Tucson, AZ

      Christopherson, Gary; Boyer, Jessica Caitlin (The University of Arizona., 2021-08-20)
      Urban tree canopy provides essential ecosystem services to cities, from improving human wellbeing and health to reducing the urban heat island effect. However, previous studies have shown that tree canopy is often inequitably distributed. In 2019, Tucson was named the 3rd fastest-warming city in the United States. In response, the city government implemented the Tucson Million Trees initiative to help mitigate rising temperatures in the desert city. In an effort to make tree canopy more equitable, this study intends to determine what factors contribute to tree inequity in Tucson so that these factors can be considered in decision-making for tree-planting locations. Using existing data from the Pima Association of Governments, average tree canopy in each census block group was determined. This tree canopy data was tested against 26 variables commonly associated with tree inequity using exploratory regression. Regression analysis identified a seven-variable model with positive correlations between average tree canopy and population density, median household income, percent population with a bachelor’s degree, percent rental households, white population, and vacant households. The model showed negative correlations between tree canopy and percent population living alone. We hope that the results of this study can guide decision makers within the Tucson city government to prioritize block groups using the variables identified as predictors of tree canopy.

      Sanchez-Trigueros, Fernando; Carini, Kiri (The University of Arizona., 2020-05)
      As urban areas grow around the world it is important to understand whether species biodiversity can adapt to these environs. Birds are known to be indicator species of ecosystem health. Furthermore, they are relatively easy to observe. In 2001, the Tucson Bird Count (TBC) was initiated to establish a long-term monitoring effort of bird biodiversity in urban Tucson. This project investigates long-term trends in the relative abundances of six common urban Tucson bird species across land classifications using the latest National Land Cover Database products, spanning 15 years. Using zonal statistics methods to aggregate bird count data within land cover classifications, this analysis determined mean relative abundance for six species over time and across land cover types. The results found that population abundance for these species has been relatively stable over time and consistent across land classifications. While overall bird species populations have declined in North America, in urban Tucson, birds are adapting. Further analysis of the TBC is needed to gain insight into species distribution and the complexities of urban habitats.
    • Traces of Existence: Evidence of Prehistoric Populations in the Cibola National Forest of New Mexico

      Lukinbeal, Christopher; Gregory, Teresa L. (The University of Arizona., 2016-12)
      Is there more we can learn about the movement of prehistoric Puebloan people during the A.D. 900–1400 time period? In those moments of time when small groups of people dispersed across the landscape and formed aggregated communities. Some of the answers lie in the generally understudied landscape of the federally protected Cibola National Forest in west-central New Mexico. This area is on the eastern periphery of a well-documented Zuni region, and preliminary archaeological site data revealed the potential to further that knowledge. During a 10-day pedestrian survey, 42 archaeological sites containing a variety of traditional Zuni and local Lion Mountain pottery types were recorded. The presence of these Puebloan peoples was confirmed through analysis of the ceramics using the accepted Stanley South Mean Ceramic Dating techniques. Patterns of site locations dating from the Pueblo II to Pueblo IV time period were evaluated using ESRI ArcGIS mapping software. Specific data analysis including nearest neighbor, euclidean distance, and least cost analysis were used to relate the archaeological sites to each other and to the Pueblo communities in the southwest. This recently discovered settlement area near Lion Mountain revealed remnants of past Zuni populations and is further evidence of the expansion of these prehistoric peoples. The pottery shreds discovered at those sites, along with the architecture and specific kiva types, links the distinctive aggregated Zuni and Lion Mountain Communities together and allows for further investigations to explore settlement organization, exchange networks, and a facet of other archaeological questions.

      Mason, Jennifer; Youngstrum, Gavin (The University of Arizona., 2021-08)
      California has been in a drought since the year 2000 and is now considered to be in a “megadrought” (Borunda, 2021). Dead and weak trees are susceptible to native bark beetles and as the drought continues to create more vulnerable trees, the bark beetle population has been increasing, causing more tree mortality (Rosner, 2020). Giant sequoia trees are the largest trees on Earth and live for thousands of years (“Giant Sequoias”, 2021). Scientist have seen not a severe increase in sequoia tree mortality due to the drought but have seen a “die-back” in their foliage and canopy loss caused by low water stress (“Leaf to Landscape”, 2016). Fire is an important part to the life cycle of giant sequoia trees, and they have been known to survive through many fires throughout their existence (“Giant Sequoias and Fire”, n.d.). However, with an increase in forest fire fuel from the drought, rising temperatures causing dryer tinder and many years of fire suppression, fires are getting unnaturally hotter and stronger, putting sequoia trees at risk (Fox, 2021). When scientists noticed their dying foliage and canopy loss, the Leaf to Landscape Project was created through partnership with multiple federal agencies and universities to study the giant sequoia trees health (“Leaf to Landscape”, 2016). The project collected tree data by flying an aircraft over Sequoia and Kings Canyon National Park using LiDAR technology (Nydick, 2018). My project utilizes the LiDAR data to analyze dead tree clusters and their proximity to giant sequoia groves using a variety of cluster finding techniques using ArcGIS Pro. Locating dead tree clusters will help assist with future fire planning for the protection of sequoia trees.

      Mason, Jennifer; Ali, Abdelrhman (The University of Arizona., 2022-05-02)
      Parks play an essential environmental and cultural function by improving the quality of life and creating valuable green space. Providing new parkland with adequate distribution and accessibility can assist in planning and development and enhance recreation projects. The Parks and Recreation Department in Tucson needs to identify and evaluate acquisitions to make informed decisions on building new parks. Doing that will provide value and benefits to the system and grow equitable access to the parks —it also aligns with other city goals to understand potential priorities of expanding the parks for underserved areas. A comprehensive acquisition strategy was formulated based on several factors to evaluate and prioritize parkland opportunities that ensure the parks are equally distributed. Using existing data from The Trust for Public Land, Pima Association of Governments, and other datasets from the City of Tucson's open data portal, ranked suitability analysis was used to find suitable areas for new parks. The analysis gave us a classification of all the possible places that can be considered appropriate and the rank of their importance. Moreover, Model Builder was utilized to update and automate the individual factors for future analysis. The outcomes of this study will provide the city with a roadmap for acquiring land for parks that meet the community's needs.
    • Understanding Patterns of Extraterrestrial Phenomena: An Exploratory Spatial Analysis of UFO Sightings Throughout the Contiguous United States from 1910-2014

      Lukinbeal, Chris; Prichett, Hannajane (The University of Arizona., 2021-08)
      Are humans alone in the universe? It is one of the most profound existential questions of all time. It is a question that this project regrettably will not answer. We all want to know if UFOs are real because not understanding the unexplained is uncomfortable. Analyses in this project seeks to uncover consistent patterns in the reported sightings of extraterrestrial phenomena in the contiguous United States in the last century. The purpose of this master’s project is to analyze data to look for patterns and relationships between UFO sightings and population density, population movement over the last century, and UFO sightings relationships to military installations across the Contiguous United States. To do so, tabular data was geocoded, and a geodatabase was established reflecting sightings between 1910 and 2014. The points were clipped to the Contiguous United States and analysis of the data focused on density and buffer analyses to examine population density relationships, mean center for population movement through time, and buffer analyses to examine sightings relationships to military installations. Results tend to show a relationship between population density and increased sightings of UFOs. No conclusive results showing temporal patterns related to a mean center analysis and mixed results related to military installations were found. GIS based research on UFOs is an important and growing field of study. This Masters Project contributes to helping us better understand UFO data from a spatial science perspective.
    • Using ArcGIS Dashboards To Monitor Scheduled Python Geoprocessing Scripts

      Sanchez Trigueros, Fernando; Montes, Celso (The University of Arizona., 2022-05)
      There is a need in Pima County’s Information Technology Department, Geographic Information Systems Division for visualizing the status of GIS scheduled Python jobs that run on various servers throughout the day and night. Most scheduled job owners get notified if there is a problem with the script. However, end users of the data may not necessarily be notified that the data they are viewing did not update. This leads to the end users being perplexed on why their edits made the day before are not visible. The solution was to create a Python module called PC_Monitor that the script owner imports into the beginning of an existing or new script that is executed at the end of the script in either its own try, except statement or at the end of a finally statement. Parameters need to be passed into one of the module’s functions to successfully update the database table. The database table is then used for visualizing the status of the script using ArcGIS Dashboards widgets. The module captures various information programmatically using user inputs. Most importantly, the module captures and records the status of the script (Success, Finished with Warnings, or Failed) and the first 255 characters of the status message for Finished with Warnings and Failed. The module has been successful in various test situations on multiple servers. The PC_Monitor module alongside the ArcGIS Dashboard will help our organization’s GIS users to visually monitor the status of Python scripts, keep track of Python scripts, and the effect those scripts have on data sets.
    • Using Classification and Regression Tree and Valley Bottom Modeling Techniques to Identify Riparian Vegetation in Pinal County, Arizona

      van Leeuwen, Willem J.D.; Hickson, Benjamin (The University of Arizona., 2015-01-01)
      The ecological value and functionality of riparian systems along ephemeral, intermittent, and perennial streams in the Southwest is well established. In Pinal County, Arizona the existing datasets available to environmental managers and governing bodies drastically underestimate the extent and presence of riparian zones. This study addresses the issue through the use of remote sensing land cover classification techniques. Landsat 8 data, topographic data, and high-resolution color infrared (CIR) imagery, and several derived vegetation indices are used to construct a classification and regression tree (CART) model. Using training data, the CART model is used for the identification and delineation of basic land cover classes across the County. Woody annual and perennial species are identified and associated to riparian zones using a valley bottom model (VBM) developed by the United States Department of Agriculture. The CART model (kappa value of 0.76) found that 929 square-miles of annual vegetation and 651 square-miles of perennial vegetation are present across Pinal County. Annual and perennial vegetation classifications are assessed for density using a 0.33 acre moving window. The density values for both classes are then used in conjunction to differentiate upland, xeroriparian, mesoriparian, and hydropriarian vegetation zones. Vegetation zones are clipped to regions where the VBM identifies valley bottom probability to be 62 percent or greater. The results generated provide a sufficiently comprehensive dataset that gives County managers and environmental professionals improved insight into the presence and distribution of important riparian habitats.
    • Using Open-Source Python Scripting to Update Fire Perimeter Datasets for the USGS

      Korgaonkar, Yoga; Jones, Dallin (The University of Arizona., 2022)
      As occurrence and intensity of wildfires in the United States increases, the need for a centralized fire perimeter dataset is crucial for ecosystem, fire and other disciplinary analyses. In late 2021, the Combined wildland fire datasets for the United States and certain territories, 1800s-Present was created by the USGS to fill the need for a single multi agency and year dataset. While this dataset improves the ease of obtaining wildfire data; errors and assumptions create inaccuracies in the dataset that hinders the usability of the data. In response, open-source python libraries are used to iterate over the data and correctly identify fire perimeters based on decision tree methodology, calculated by fire ecologists. This script successfully identifies smaller fires that would otherwise be grouped with larger focal fires. The final python script successfully identifies separate fire perimeters in the same calendar year, increasing the datasets accuracy and allowing smaller fires to be further analyzed.
    • Using Spectral Indices To Determine the Effects of the Summer 2021 North American Heat Wave at Mount Rainier, Washington

      Mason, Jennifer; Almekinder, Kyle (The University of Arizona., 2022-04-28)
      Quality of life at Mount Rainier and the surrounding region is dependent on annual snowpack and subsequent snowmelt. Winter storm observations, snowpack, and the rate of snowmelt all play critical roles in determining the health of the environment. To help analyze these factors, users and consumers rely on remotely sensed data to analyze the past, present, and future of the area. The Normalized Difference Snow Index (NDSI) and Normalized Difference Vegetation Index (NDVI), collected from satellite imagery, are two spectral indices used with analyzing snowpack and vegetation health to assist risk mitigation for wildfires, glacial change, and river ecosystems. This project used NDSI and NDVI to determine if the 2021 North American heat wave had any significant effects on vegetation health, snowpack, and glacial size over a five-year study period. Landsat 8 satellite imagery was acquired, corrected for any atmospheric bias, and processed through GIS techniques. Despite yearly fluctuation of warmer and cooler years, results show a progressive increase in snowmelt with 2021 showing the highest percentage during the study period and the highest differential from the mean of all years in the study. Vegetation labeled as “Healthy” saw the biggest decrease between consecutive years from 2020-2021. Also in 2021, Mount Rainier saw its glaciers recede to their lowest total area since 2005. Conclusions show that general warming trends are occurring in the Pacific Northwest and the heat wave exacerbated total glacial area, total snow area, and vegetation health. This Masters project contributes to future extreme weather anomalies and related results.
    • Using Suitability and Proximity Analysis to Discover Houston's Accessibility via Roadways and Public Transportation

      Lagarde, Ethan (The University of Arizona., 2015)
      Houston is one of the fastest growing metropolis’ in the country. Driving this growth is the oil and gas industry and also the Texas Medical Center, the world’s largest medical center. With such growth comes various problems. One of the leading problems according to its citizens in 2014 was traffic and the lack of access to public transportation. This project aims to help find solutions to this problem by locating areas that could help improve public transportation access and take a look at Houston’s accessibility via roadways. Using datasets from various Houston agencies such as the City of Houston and the Houston-Galveston Area Council, overlay analysis was used to help find prime areas that could be improved. Using ESRI ArcMap, models were completed in order to automate the analysis process. Tools such as raster conversion, Euclidean distance, zonal stats as table, and reclassify were used. In order to analyze Houston accessibility via the roadways, ArcGIS Online was used. Several Proximity analyses were run in order to view various types of dating dealing with the accessibility of Houston using roadways. The results show areas that do not currently have access to public transportation and areas that would be suitable locations for improvements based on different criteria. For roadway access, the results show average commute times, drive-time accessibility, and freeway access. This will allow for the accessibility of Houston to be shown whether it is by public transportation or by roadway.

      Mason, Jennifer; Tala (The University of Arizona., 2022-04-29)
      Climate change will likely lead to major changes in plant distribution and thus in biomes and habitats. Humans and other species will be affected as our ecology is intimately linked not only to climate but also to habitat availability. This study looks at the vegetative changes within the Bureau of Land Management’s Areas of Critical Environmental Concern designated areas. These areas are in Rio Arriba County and Taos County in New Mexico and the study is from 2000 and 2020 to determine if the Bureau of Land Management’s protective measures have helped mitigate drought effects within the region. The study area includes the Areas of Critical Environmental Concern designated areas of Lower Gorge, Copper Hill, Ojo Caliente, and the Taos Plateau, which cover approximately 327,040 acres within the two study counties. Using surface reflectance and Normalized Difference Vegetation Index analysis, datasets are compared for changes in vegetation health over 5-year increments – 2000, 2005, 2010, 2015, and 2020. Datasets are also compared between 2000 and 2020. Although precipitation levels fluctuate over the temporal extents and vegetation changes accordingly, overall, there has been a decline in vegetative cover over the entire study area. These vegetation changes are most drastic within the Ojo Caliente and Lower Gorge/Copper Hill Areas of Critical Environmental Concern. More research is needed to determine whether the Bureau of Land Management’s protective measures, or lack thereof, have contributed to the decline in vegetation, or if it has to do with the overall effects of long-term drought and climate change.
    • Where am I? Developing Spatial Thinking Skills

      Lukinbeal, Chris; Glueck, Mary (The University of Arizona., 2020-05)
      Middle school students are inundated with a plethora of geographic and GIS instructional resources; however, these students often lack the spatial thinking skills necessary to orient themselves in space and make meaningful geographic connections to the world. The question, “Where am I?”, is challenging without an understanding of spatial orientation, distance, and connections. Developing geographic literacy, even geographic media literacy, being able to locate and connect themselves in the world, is critical to their greater understandings. With this Master’s Project, I document a learner-centered exercise that develops spatial thinking skills. Spatial thinking combines spatial concepts, visualization, and reasoning. Spatial thinking reaches beyond answering “where” with a simple “here” to consider personal awareness of spatial orientation along with spatial connections, and pattern recognition at different spatial scales for problem-solving, decision-making, or policy purposes. Middle school, a time of growth in student understandings from concrete to abstract, is an optimal stage to advance and implement spatial thinking skills. Furthermore, curriculum standards focus on crosscutting concepts of patterns, change, and scale, providing ample opportunity for increasing spatial understandings. This research project involved a sixty-five student cohort that was guided through a geographic inquiry process to build spatial thinking skills and conceptual understandings by orienting themselves in the classroom, applying historical survey methods to create a grid map of the school courtyard, and extending this to GIS-based virtual transects of student-selected connections. Outcomes indicate considerable growth in student spatial thinking skills and understandings. Their knowledge will be applied to future Earth Science investigations ensuring strong engagement and greater spatial understandings. Keywords: Geographic education, reasoning, spatial connections, spatial orientation, visualization