Geographic Information Sciences Commons^™

Tradeoffs Of Generalization, Kyra M. Abrams, Peter T. Darch

I-GUIDE Forum

Models used in geospatial data science are often built and optimized for a specific local context, such as a particular location at a point in time. However, upon publication, these models may be generalized beyond this context, reused in research simulating or predicting other times and places. Without sufficient information or documentation, bias embedded in these models can in turn result in bias in the reuser’s research outputs. Drawing on a long-term qualitative case study of aging dams researchers and developers of models used by these researchers, we find significant documentation gaps. We combine a literature-based genealogy with interviews with …

Data-Intensive Convergence Science For Analyzing Place-Based Spatial Accessibility, Alexander C. Michels, Shaowen Wang

I-GUIDE Forum

Place-based spatial accessibility is a critical tool for measuring the health, resilience, and sustainability of communities. Accessibility methods are employed by a wide range of fields to measure access to food, healthcare, infrastructure and other critical needs. While measures of access are relatively simple, they attempt to capture the complexities of human mobility and spatial decision-making to assess how well populations are served by the infrastructure, resources, and services at their disposal. This paper describes four key areas where data-intensive convergence science can revolutionize our understanding of place-based spatial accessibility by addressing issues of scale, spatial impedance, diversity, and accessibility. …

Being Open About Oer: Perceptions, Use, And Impact, Treasa Bane, Dorris Scott

WashU Libraries Presentations

In this session, the presenters will describe the experience of adopting an open educational resource for a course, the motivation to adapt that open educational resource, and the steps they took to manage an OER adaptation project . The participants will be engaged with prompting questions and conversation points during each section of the presentation, and they will be given time to brainstorm and discuss the challenges, motivations, tools, and support they have at their own campuses to take on similar projects.

Challenges Of Using More Precise Temporal And Spatial Resolution Of Remote Sensing Data For Surface Water Quality Monitoring, Ivan Rykin

Dartmouth College Master’s Theses

Monitoring river suspended sediment concentration (SSC) is critical for environmental challenges such as understanding the fate of thawed permafrost sediment and its impact on global carbon cycling. However, traditional SSC monitoring using Landsat imagery is limited by spatial and temporal constraints, particularly for narrow rivers in cloudy and/or snowy regions.

This study investigates the use of higher spatial (3 m) and temporal (daily) resolution satellite imagery from the PlanetScope constellation to estimate SSC in remote rivers such as those in the Arctic. I compare the performance of PlanetScope’s spectral resolution (4 and 8 bands) with Landsat 7. Merging data from …

Conducting Structure-From-Motion (Sfm) Modeling Of Freshwater Environments Using Unpiloted Aerial Systems (Uas): Challenges And Lessons Learned, Benjamin T. Fraser, Christine L. Bunyon, Russell G. Congalton

Faculty Publications

The pairing of Unpiloted Aerial Systems (UAS) and Structure from Motion (SfM) has provided new capabilities for modeling freshwater environments. Applications of UAS-SfM range from water quality monitoring to the mapping of aquatic vegetation. The models produced provide users with the ability to analyze features at ultra-high-resolutions and across scales not easily achieved through in situ sampling. Despite the demonstrated benefits of UAS-SfM in freshwater and other natural resource disciplines, there remain fundamental technical challenges in the modeling of environments with homogenous surfaces (e.g., water). In this research, the effectiveness of several image collection and processing approaches for the modelling …

How Short-Term Rentals Impact Summit County, Colorado, Spatially And Economically: A Gis Analysis, Hanna Gilhooley

Geography and the Environment: Graduate Student Capstones

Summit County, Colorado, is experiencing a housing crisis influenced by the rise of short-term rentals (STRs). This project investigates how STRs spatially and economically impact the county. STRs are regarded as a reason for the housing crisis as they take away long-term housing from locals and increase housing market prices. Locals are forced to look for housing in neighboring counties such as Clear Creek, Eagle, Grand, Lake, and Park. Geographic Information Systems (GIS) can be used to analyze the spatial and economic impact of STRs in Summit County. Total population, median household income and STR locations are analyzed in ArcGIS …

A Comparative Gis Analysis Of United And Southwest Airlines Route Networks, Robert Brown

Geography and the Environment: Graduate Student Capstones

This GIS project explores the relationship between airline route networks and flight delays for two U.S. Airlines. Using data obtained from the Bureau of Transportation Statistics (BTS), route networks were created for United and Southwest Airlines showing all flights that each carrier reported in 2023. The airlines of interest were selected due to their opposing route network types; commonly referred to as a hub-and-spoke (HS) and a point-to-point (PTP) route network, respectively. Link charts were created to calculate centrality metrics quantifying these networks, and flight delay data were manipulated and summarized to develop an ArcGIS Dashboard with which any ArcGIS …

Wolverine Habitat Suitability Analysis In Lake County, Colorado, Using Gis, Jake Hostnik

Geography and the Environment: Graduate Student Capstones

This project explores the reintroduction of the wolverine (Gulo gulo luscus) to Colorado’s mountainous regions, where the species has been extirpated due to habitat destruction and human activities. The study uses Geographic Information Systems (GIS) to identify optimal habitats for wolverine reintroduction, considering factors like snowpack duration, prey availability, and human disturbance. By creating a GIS-based habitat suitability model, this research will guide conservationists in selecting reintroduction sites. The project addresses the species' role in maintaining alpine ecosystem balance and contributes to the broader understanding of biodiversity restoration in the face of climate change. Results will inform future conservation planning …

Chronic Obstructive Pulmonary Disease Hot Spots In Mississippi, Taylor Jansen, Elizabeth Dugan

Journal of Public Health in the Deep South

Abstract

Introduction. Chronic obstructive pulmonary disease (COPD) is the sixth leading cause of death in the US and approximately 10% of people 65 years and older have COPD. This study examines the association of geographic-level risk factors with chronic obstructive pulmonary disease (COPD) prevalence using spatial-based analyses with the goal of identifying risk factors associated with county-level COPD and to identify communities at risk.

Methods. The study sample consisted of all N=82 counties in Mississippi and all data is reported at the county level. All measures were drawn from the 2023 Mississippi Healthy Aging Data Report. A hot spot …

Gps Accuracy Of Smartphones For Crowdsourcing Research, Derron L. Dike

Master of Science in Environmental Sciences and Management Projects

ABSTRACT GPS Accuracy of Smartphones for Crowdsourcing Research Derron Dike Utilizing crowdsourcing with smartphones as a method for field data collection can contribute an array of data for scientific studies and land management applications. This study used crowdsourcing to examine smartphone built-in GPS performance for providing location-specific information with potential forestry applications. The usability of smartphones for GPS data collection in forestry studies or other practical applications is dependent on the level of accuracy required for those applications. A Smartphone Accuracy Trial was designed to test the GPS accuracy performance of current smartphones. Participants used the ArcGIS Field Maps application …

A Study Of The Impact And Mitigation Strategies For Community-Defined Historic Places At Immediate (Within Three Decades) Risk Of Sea Level Rise, Isaac Quaye

All Theses

The rising sea level casts formidable threats on community-based historic places within coastal communities. These community-defined historic places derive their meaning from local values and are more recognized within the local community. Unlike recognized iconic historic places, these resources are confronted with inadequate resources to address the impacts of punctuated climate events. This study investigates the imminent threats posed by sea level rise (SLR) to community-defined historic places within the next three decades (2025) and explores mitigation strategies proposed by stakeholders. The study used a GIS-based (enhanced bathtub model) to model the impact of coastal inundation on three historic places …

Paths Of Least Resistance: A Geospatial Analysis Of The Integration Of Mississippian Communities In The Northwest Arkansas Ozarks, Joseph Jilek

Anthropology Undergraduate Honors Theses

During the Mississippi period (ca. AD 1050-1500), native groups occupying bluff shelters in the Northwest Arkansas Ozarks constructed three similarly sized mound-and-plaza centers: Goforth-Saindon (3BE0245), Collins (3WA0001), and Huntsville (3MA0022). Similarities in size and number of mounds suggests none rose to a position of power over the other and each integrated a separate community. Previous research hypothesizes that communities in emergent complex societies such as these are best defined by those who you interact with regularly, with mound centers less than a day’s travel from each other likely integrating the same communities. This study uses least-cost analysis, generating likely travel …

Dengue And Climate Change: Assessing Potential Future Areas Of Concern For Transmission In The United States, Matthew Beer

Electronic Theses and Dissertations

Background: Global climate change severely impacts human life, particularly health, as rising temperatures and extreme weather affect physical and mental well-being. Climate change can also alter the risk factors and epidemiology of infectious diseases, notably vector-borne diseases (VBDs), including those transmitted by mosquitoes. The Aedes mosquito, responsible for dengue, poses a significant threat due to its prevalence vector. Dengue prevention lacks effective methods beyond vector control, and the current vaccine has limitations, emphasizing the need for intensified research and prevention strategies to mitigate the expanding dengue burden worldwide. The goal of these studies was to establish a novel risk index …

A Comparison Of Maxent Models For Aedes Aegypti Species Distribution In South America Utilizing Different Bioclimatic And Environmental Variables, Matthew Beer

Electronic Theses and Dissertations

Aedes aegypti is the principal vector for dengue transmission across large areas of the world. Understanding where this critically important vector lives is paramount to preventing the continued expansion of dengue globally. Using 1981-2010 bioclimatic (bioclim) variables, as well as additional environmental variables and elevation data, multiple MaxEnt models were constructed for Ae. aegypti within the South American continent to identify ecologically important variables and areas of persistent high suitability. All models had acceptable AUC scores (> 0.70), indicating accurate model fitting. Annual mean precipitation and temperature were found to be important model variables; however, when added, humidity became the …

Geospatial Analysis Of Environmental, Tick, And Host Interactions With Rocky Mountain Spotted Fever In The Southwestern United States, Al Ekram Elahee Hridoy

Geography ETDs

This study examines the spatiotemporal distribution and determinants of Rocky Mountain Spotted Fever (RMSF) incidence in Arizona from 2006 to 2021. Utilizing climate variables, land cover types, and socio-economic indicators, we employed Negative Binomial Regression, Spatial autocorrelation, and Random Forest-based classification to identify key predictors and patterns of RMSF spread. Results indicate positive correlations between RMSF incidence and precipitation and shrub cover, while veterinary access, forest cover, and relative humidity show negative associations. Spatial analysis revealed significant case clustering, with limited veterinary access associated with higher RMSF incidence. A Random Forest-based predictive model was developed to identify potential tick-host interactions, …

Implementing Interdisciplinary Sustainability Education With The Food-Energy-Water (Few) Nexus, Chelsie Romulo, Bhawani Venkataraman, Susan Caplow, Shamili Ajgaonkar, Craig R. Allen, Aavudai Anandhi, Steven W. Anderson, Caterina Belle Azzarello, Katja Brundiers, Eunice Blavascunas, Jenny M. Dauer, Daniel L. Druckenbrod, Ennea Fairchild, Lydia R. Horne, Kyungsun Lee, Marizvkuru Mwale, John Mischler, Emily Pappo, Nirav S. Patel, Nicole D. Sintov, Carla S. Ramsdell, Shirley G. Vincent

GGS Faculty Publications

Growth in the green jobs sector has increased demand for college graduates who are prepared to enter the workforce with interdisciplinary sustainability skills. Simultaneously, scholarly calls for interdisciplinary collaboration in the service of addressing the societal challenges of enhancing resilience and sustainability have also increased in recent years. However, developing, executing, and assessing interdisciplinary content and skills at the post-secondary level has been challenging. The objective of this paper is to offer the Food-Energy-Water (FEW) Nexus as a powerful way to achieve sustainability competencies and matriculate graduates who will be equipped to facilitate the transformation of the global society by …

Critical Geospatial Data Science: Principles For Curating, Analyzing, And Sharing Geospatial Data, Daniel Beene

Geography ETDs

Critical geospatial data science (CGDS) offers principles for engaging with geospatial data, methods, and translation by pulling from critical epistemologies in geography. CGDS interrogates objective “truths” in science by actively engaging in critique of geospatial data and methodologies. Specifically, CGDS contends with the political context and motivations behind geospatial data science (GDS) while using GDS methods to understand how social-spatial arrangements manifest and are reinforced through data. CGDS explicitly aims to inform practices for criticality from within GDS and provides opportunities for multidisciplinary research that incorporates social theories, contextualizes geospatial data, and critically evaluates the effects and ethics of (under)representation …

Business Operators’ Perception Of The Impact Of The Portuguese Way Of St. James, Paula Remoaldo, Eduardo Duque, Vítor Ribeiro, José Cadima Ribeiro, Hélder Silva Lopes, Sandro Ferreira, Cátia Faria

International Journal of Religious Tourism and Pilgrimage

This research aims to analyse business operators’ perception of the impact of the Portuguese Way of St. James and to assess the landscape situation along a total section of 115 kilometres. Perceptions were collected in a survey of 112 small operators between 2020 and 2021. The diversity and singular components of the landscape make it a pleasant route to experience, where pilgrims have the possibility to improve wellbeing, and enjoy the landscape. Operators have profited from the significant increase in the number of pilgrims walking along the Way and claim that they aim to continue their operations.

A Geospatial And Machine Learning Framework For Forecasting Ground Level Ozone Pollution, William J. Keenan

Electronic Theses and Dissertations

The major detrimental health effects of ground-level ozone (GLO) pollution make it imperative that both policy makers and ordinary citizens have access to high accuracy, high-resolution forecasts of their local area. Recently, advancements in computing power have made it possible to apply artificial intelligence (AI) techniques to a variety of big data modelling problems, including GLO forecasting and estimation. Of these AI methods, deep neural networks (DNN) have demonstrated the highest accuracy due to their ability extract non-linear relationships from high dimensional, noisy data inputs.

This research effort uses novel data sources, namely NOAA’s High Resolution Rapid Refresh (HRRR) meteorology …

Foreign Object Debris: A Spatial Analysis Of Wildlife At Seatac Airport, Eli Elias

Geography and the Environment: Graduate Student Capstones

This study investigates the relationship between birds and prey within the airport environment at Seattle-Tacoma International Airport (SEATAC). In 2023, instances of bird and prey activity near Runway 16C/34C were recorded using Foreign Object Debris (FOD) detection radar. The study stems from the importance of safety within the airport environment and analyzing these relationships to better protect people and mitigate aircraft damage. Runway 16C/34C is the runway of focus as it is the only runway equipped with FOD detection radar. Temperature and rainfall averages acquired from the National Weather Service (NWS) were also used to expand this analysis. The results …