Geographic Information Sciences Commons^™

Statistical Downscaling Of Climate Datasets With Deep Generative Model And Bayesian Inference, Guiye Li, Guofeng Cao

I-GUIDE Forum

Facing the challenges of global climate change, precise and high spatial resolution climate data are crucial and in pressing need for scientific research and analysis. However, most existing datasets are only available with very coarse spatial resolution and demand large-scale resolution enhancement. Meanwhile, climate datasets own much more intricate textures than natural images. Statistical downscaling or super-resolution (SR) with the deep-learning-based generative model might be a promising approach to address these challenges. It is worth noting that a learned Bayesian reconstruction with generative models (L-BRGM) method was proposed recently. The proposed Bayesian deep learning framework employs a single pre-trained generative …

Understanding Complex Socio-Environmental Systems With Spatial Agent-Based Models, Rebecca C. Vandewalle, Alexander Michels, Furqan Baig, Shaowen Wang

I-GUIDE Forum

Our increasingly connected world is faced with complex socio-environmental problems (e.g., biodiversity loss, climate change, and food insecurity). Tackling these problems requires cross- disciplinary approaches that examine the problems based on synergistic spatial and system thinking. Spatial Agent-Based Models (SABMs) represent a powerful approach to understanding complex socio-environmental systems. However, research on SABMs and associated complex problem solving face grand challenges that must be overcome to effectively unleash the power of SABMs enabled by cyber-based geographic information science and systems (cyberGIS). This paper describes four such grand challenges —reproducibility, scalability, communication, and accessibility. Resolving these challenges will enable new spatial …

Communicating Uncertainty And Cataloging Bias In Spatial Data Science Education, Peter Kedron, Jiahua Chen

I-GUIDE Forum

Uncertainty is an unavoidable part of any spatial analysis, which makes quantifying and communicating uncertainty a requirement of any spatial data science study. However, current curricula leave students understanding the importance of uncertainty and concerned about potential bias, but without an actionable framework to improve their workflows or inferences. We propose a framework rooted in Bloom’s Taxonomy for introducing these concepts to spatial data science students.

A Convergence Framework For Integrating Cybergis Education And Research On I-Guide Platform, Fangzheng Lyu, Furqan Baig, Yunfan Kang, Erick Li, Anand Padmanabhan, Shaowen Wang

I-GUIDE Forum

This paper described Data with Notebooks as a convergence framework for integrating cyberGIS education and research on the I-GUIDE Platform. The I-GUIDE Platform provides rich geospatial data and computing resources and adheres to FAIR (findable, accessible, interoperable, and reusable) data principles. The framework enhances these capabilities by harnessing scalable and reproducible geospatial analytics. Specifically, this framework supports the development of interactive cyberGIS education and research Jupyter Notebooks centered around geospatial datasets. A case study demonstrates the application of the framework, showing six cyberGIS research notebooks and four cyberGIS education notebooks based on a Twitter dataset. The case study and underlying …

Building Blocks For Geospatial Software Education Using The I-Guide Platform, Rebecca C. Vandewalle, Alexander Michels, Zhiyuan Li, Nattapon Jaroenchai, Shaowen Wang

I-GUIDE Forum

By combining advanced cyberinfrastructure with geospatial analysis capabilities and resources in an accessible online environment, the I-GUIDE Platform has great potential for geospatial computing focused education. However, learning occurs in different settings and contexts, both formal and informal. For I-GUIDE Platform to be successful, it should have the flexibility to support a variety of educational needs. In this paper, we argue for an expanded set of front-end building blocks to support diverse education and research use-cases, building on existing cyberGIS capabilities and Jupyter backend. We draw from experience working with the CyberGISX platform as an education tool in different learning …

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.

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Visualization Of Indiana And Northern Long-Eared Bats Using Spline Surfaces To Enable Targeted Land Management, Devin Escue

Geography and the Environment: Graduate Student Capstones

This project introduces a Bat Visualization Tool to help manage habitats for threatened bat species while considering broader ecosystem dynamics. It integrates data from acoustic bat surveys at the Corriell Nature Preserve in Iowa. The tool attaches spatial context to non-spatial survey data, weights species calls based on statistical p-values, and creates visual bat species distribution maps using spline surfaces. It also generates future survey locations based on these patterns. By using geospatial analysis and statistics, the tool identifies priority areas for conservation actions, focusing on factors like forest composition, roosting preferences, and land cover types that affect bat habitat …

Gis-Based Dashboard For Data Analysis And Visualization At The Water Hub In Franschhoek, South Africa, Liliana Rosa Simon

Geography and the Environment: Graduate Student Capstones

This capstone project analyzes the land use change in the Franschhoek Valley, South Africa, and implements this information into an ArcGIS Experience Builder Dashboard. The development of an ArcGIS Experience Builder is utilized as a tool for improved spatial data communication at The Water Hub. An increase in urban development in the informal settlement upstream of the Stiebeuel River in the catchment basin north of the Water Hub research institute is found. The capstone uses geographic information systems, remote sensing, and ArcGIS Experience Builder to integrate spatial data into the Water Hub’s standard operating procedures. It highlights the importance of …

Wasted Space: Using Parking Lots & Vacant Land To Improve Neighborhood Completeness, Ryan Martyn

Hatfield Graduate Journal of Public Affairs

This study conducts a spatial analysis of Portland, Oregon, focusing on leveraging underutilized areas like parking lots and vacant land—termed "wasted space"—to improve the city's completeness. Central to this investigation is the concept of a "complete neighborhood," characterized by access to daily necessities within convenient active transportation trip. This comprehensive idea encompasses walkability, equitable access to services, and sustainability.

This paper aims to redefine the concept of a complete neighborhood with precision and delve into its implications. The research looks at five regional, town, and neighborhood centers as defined by the city of Portland. These centers act as pivotal hubs …

“I Had To Go There For My Own Safety” Negotiations Of Access And Autonomy Among Dc Birth Settings, Elizabeth Avery Borgmann

Geography Undergraduate Senior Theses

Childbirth experiences are shaped by spatial context. This study considers the relationships between access to, selection of, and experiences with labor and delivery care among Black birthing people in Washington, DC. Informed by Reproductive Justice and reproductive geographies frameworks, I employ a mixed methods GIS design that integrates mapping of potential spatial access with qualitative analysis of community members’ lived experiences. On the quantitative side, nearest-neighbor and 2-step floating catchment area analyses reveal an east-west gradient of potential spatial access to labor and delivery wards, with low access concentrated in predominantly Black and low-income census tracts of Wards 5, 7, …

Spatial Targeting Of Irrigation Development And Water Resource Management To Mitigate Vector-Borne Disease, April Frake, Brad Peter, Grivin Chipula, Joseph Messina

Geosciences Faculty Publications and Presentations

Scaling irrigated agriculture is a global strategy to mitigate food insecurity concerns. While expanding irrigated agriculture is critical to meeting food production demands, it is important to consider how these land use and land cover changes (LULCC) may alter the water resources of landscapes and impact the spatiotemporal epidemiology of disease. Here, a generalizable method is presented to inform irrigation development decision-making aimed at increasing crop production through irrigation while simultaneously mitigating malaria risk to surrounding communities. Changes to the spatiotemporal patterns of malaria vector (Anopheles gambiae s.s.) suitability, driven by irrigated agricultural expansion, are presented for Malawi's rainy and …