Digital Commons Network^™

Source Origins Of Hunter-Harvested Waterfowl In Arkansas And Louisiana, Shannon C. Stemaly

LSU Master's Theses

Understanding variability in breeding origins of harvested waterfowl is important for effective population management and regional conservation. Band-recovery data are often used to estimate harvest derivation and inform resource allocation for cross-seasonal conservation. However, uneven spatial and temporal banding effort across species' breeding ranges may result in an incomplete understanding of summer origins and recruitment, particularly if portions of the breeding range are inaccessible. Analysis of stable-hydrogen isotope ratios in duck feathers (δ²H_f) provides an alternative method for identifying source origins of unmarked populations since environmental deuterium values follow a predictable latitudinal gradient across North …

The Evolution Of Global Gold And Copper Trade Networks, Oleksandr Hulianskyi

Northeast Journal of Complex Systems (NEJCS)

Gold and copper have emerged as two of the most vital commodities in global trade. Despite serving distinct purposes, their international trade networks reveal interconnected patterns, critical to understanding the dynamics of global economics. This paper studies these attributes and their evolution during the last 36 years for both metals and finds correlations between them. The first part of the research is focused on the sustainability of networks through efficiency and robustness indexes; the second part is dedicated to interconnectedness – the Louvain and Bayesian SBM algorithms, partition, and modularity instruments are used. Community detection algorithms provide valuable insights into …

First Insight On The Genesis Of Iron Oxide-Hydroxide Biospeleothems In Rancho Chico Lava Tube, Mexico, Rafael López-Martínez, Elizabeth Solleiro-Rebolledo, Rocio Alcántara-Hernández, Teresa Pi Puig, Sergey Sedov, Daisy Valera Fernández, M. Nayeli Luis-Vargas, Yasmany Lima Vera, Jesús Solé, Ramon Espinasa-Pereña

International Journal of Speleology

Iron is a common element in lava tube systems, typically observed as thin crusts or inferred from the reddish coloration of secondary mineral deposits. In this study, we describe iron oxide-hydroxide biospeleothems discovered in the Rancho Chico Lava Tube, located within the Xalapa Monogenetic Volcanic Field in Mexico. We adopt an integrative approach combining petrography, soil micromorphology, scanning electron microscopy, mineralogy, and 16S rRNA gene metabarcoding. DNA sequencing reveals the presence of microorganisms such as Acidithiobacillus, Gallionella, and members of the Leptospirillaceae family, which may be involved in the oxidation of Fe²⁺ within the lava tube. The source …

A Modern Approach To Classifying Medieval Latin Scripts, Robert L. Lane Jr, Rafia Mirza, Robert Slater

SMU Data Science Review

Paleography, the study of historical handwriting, is essential for preserving societal understanding of cultural, social, and legal frameworks from the past. Medieval manuscripts, often exhibiting refined craftsmanship, present unique challenges to modern readers due to differences in handwriting conventions and the absence of standardized punctuation and spaces. These texts hold valuable insights into the evolution of written communication, literacy, and language development. However, interpreting them requires specialized knowledge and technological solutions. Convolutional Neural Networks (CNNs) can be leveraged to classify scripts, an important step in Historical Document analysis. These models extract and analyze hierarchical features from images, addressing inconsistencies in …

The Enigmatic Samuel Aughey: Nebraska’S Pastor Naturalist, Hugh H. Genoways, Margaret R. Bolick, Mary Anne Andrei

Zea E-Books Collection

Samuel Aughey at age 39 became the first Professor of Natural Science at the new University of Nebraska in Lincoln, serving from 1871 to 1883. He was an ordained pastor of the Evangelical Lutheran Church, with an addendum degree from Pennsylvania College (now Gettysburg College) in 1856 and an A.M. degree two years later. His early pastoral work was in Pennsylvania, but in 1864 he became a home missionary to a church in Dakota City, Nebraska. Aughey’s career at the university was marked with successes and honors, but also criticism and questions about his basic knowledge of the sciences. While …

A Comprehensive Systematic Review Of Machine Learning Applications In Assessing Land Use/Cover Dynamics And Their Impact On Land Surface Temperatures, Rasool Vahid, Mohamed Aly

Environmental Dynamics Faculty Publications and Presentations

In a world experiencing rapid urbanization, the phenomenon of land surface temperature (LST) variation has invited substantial attention due to its profound impact on the environment and human well-being. Changes in land use and land cover (LULC) within urban areas significantly influence the dynamics of LST and are a major driver of urban eco-environmental change. The complex connections between LULC dynamics, LST, and climate change are investigated in this systematic review, with a focus on the combined effects of these variables and the use of Machine Learning (ML) techniques. The data in this study, based on peer-reviewed publications from the …

Mapping Responsible Workflows For Geospatial Data Science: Developing The I-Guide Data Ethics Toolkit, Peter T. Darch, Kyra M. Abrams, Ivan Y M Kong

I-GUIDE Forum

AI workflows in geospatial data science offer significant societal benefits but raise ethical, transparency, and reproducibility challenges. Current ethical frameworks and tools are often hard to integrate into daily research practice. This paper introduces the I-GUIDE Data Ethics Toolkit (DET), a lightweight suite designed for users of the NSF-funded Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE). Based on a longitudinal mixed-methods study, including surveys, interviews, and observations, we identified five design priorities: usability, anticipatory planning, distributed responsibility, comprehensive coverage, and policy compliance. We integrated existing AI and data research lifecycles into an eight-stage I-GUIDE Research Lifecycle, serving …

Evaluating The Evaluation Matrices: Integrating Spatial Assessment In Geospatial Ai Model Training And Evaluation, Fangzheng Lyu

I-GUIDE Forum

This paper examines the limitations of current evaluation metrics in GeoAI. Through two case studies on deep learning models—a building detection classification problem and a remote sensing image fusion regression problem—this paper demonstrates how traditional statistical evaluation matrices alone can be misleading in geospatial problems. The findings indicate that traditional metrics (e.g., RMSE, MAE) used in current GeoAI models can have difficulty capturing the spatial dimensions inherent to geospatial problems. This paper suggests that the model evaluation process in GeoAI should move beyond traditional evaluation matrices by integrating spatial thinking throughout the modeling pipeline—not only incorporating spatial accuracy in model …

Expanding Access To Cybergis-Compute Through Support For Heterogeneous Workflows, Alexander C. Michels, Ian Zhang, Anand Padmanabhan, John Speaks, Rebecca Vandewalle, Shaowen Wang

I-GUIDE Forum

CyberGIS-Compute is a geospatial middleware tool designed to lower technical barriers to High-Performance Computing (HPC) resources. It provides end-users with a Graphical User Interface (GUI) for submitting models to HPC and allows model developers to contribute their workflows by adding a manifest to their repositories. However, the simplification of the user interface and streamlining of model contribution have unintentionally limited the scope of models that could be run on CyberGIS-Compute. In this paper, we discuss recent developments to the CyberGIS-Compute project that are aimed at supporting a wider variety of workflows including performance enhancements, supporting additional configuration options for jobs, …

Sea Turtle Nesting On Nourished Beaches With Different Construction Designs: A Case Study In Southeast Florida, Usa., Lara Novalvos Hernandez

USF Tampa Graduate Theses and Dissertations

This study examines the influences of different beach nourishment designs and subsequent post-nourishment profile adjustments on loggerhead (Caretta caretta) and green (Chelonia mydas) sea turtles nest survival and reproductive success. Data on time-series post-nourishment beach-profile changes, positions and elevations of turtle tracks and nest/false-crawl apices, and sea turtle nest hatch/emergence success were collected on five high density nesting beaches along the east coast of Florida: Melbourne Beach, Jensen Beach, Jupiter Island Beach, Juno Beach, and South Hutchinson Island Beach. The field data collection was conducted in 2018, 2019, 2021, and 2022 with the main goal of documenting and comparing turtle …

Behavior And Land Use Of Eastern Gray Squirrels In Urban And Suburban Environments, Laura F. Engel

USF Tampa Graduate Theses and Dissertations

Urbanization has significantly altered natural habitats, impacting wildlife behavior and distribution. This study examines the behavior and land use of eastern gray squirrels (Sciurus carolinensis) in urban and suburban environments at the University of South Florida. Using a combination of point count surveys and time-activity budgets, squirrel presence was assessed in relation to tree genera, nest locations, human activity, and infrastructure. Results indicate a significant association between squirrel presence and tree genera, with a preference for Quercus species, as well as a strong positive correlation between human infrastructure and squirrel presence. However, no significant relationship was found between human presence …

Hierarchy Viz: A Visual Analytics Framework For Visualizing Hierarchical Data Using Machine Learning, Vinay Kumar Uppalapati

Theses and Dissertations

Automated visualization systems aim to generate visualizations directly from raw data with minimal user inputs. However, while existing systems focus on data visualizations mainly using line charts and scatter plots to explore the data patterns, they struggle with hierarchical data representation where data relationship is essential. Hierarchical visualization, crucial for understanding multi-level relationships, typically requires users to manually define hierarchies and have expertise in visualization tools to create meaningful representations. This makes the process complex, time-consuming, and reliant on domain knowledge. To address this, we propose HierarchyViz, an automated system that detects multiple hierarchies in raw datasets and generates intuitive …

Enhancing Cybersecurity Based On Blockchain Technology: A Systematic Review, Sarah Mohammed Shareef, Rehab Flaih Hassan

Journal of Soft Computing and Computer Applications

Cybersecurity is a crucial component of the security system that guards against unauthorized access to digital transactions. Blockchain is a decentralized ledger used to securely exchange digital currencies and conduct trades and transactions. Blockchain technology has led to significant changes in electronic transactions. The enormous potential is being exploited in many areas such as financial services, real estate, supply chain, and the Internet of Things. Despite being a security system, it has suffered from security threats to sensitive data. Phishing and 51% attacks can circumvent blockchain security, highlighting the need for thorough user education and awareness. Additionally, blockchains based on …

Elemental Analysis Of Sediments In Johnson County, Kansas: Applications In Fluvial Suspended Sediment Tracing, Kiena Campbell

Undergraduate Theses, Capstones, and Recitals

This exploratory study investigates whether bulk elemental analysis of sediment samples using inductively coupled mass spectrometry (ICP-MS) can reveal chemical signatures that identify anthropogenic contributions to sedimentation and increased fluvial suspended sediment loads, and whether these contribution sources can be identified. Human activity, urbanization, and changes in land use increase erosion, resulting in higher-than-natural suspended sediments (SS) in waterways and increasing sedimentation in reservoirs across the state of Kansas. These threats to freshwater storage capacity are especially urgent given the projected rise in freshwater demand in the Great Plains region driven by climate change. Understanding the origin of anthropogenic SS …

Analyzing Human - Nonhuman Primate Conflict Mitigation Techniques In Mto Wa Mbu, Northern Tanzania, Lil Adams

Undergraduate Theses, Capstones, and Recitals

Human-wildlife conflict is a widespread challenge faced by those living in regular contact with wildlife that can have profound impacts on livelihood outcomes for humans, wildlife, and their shared environment (Barua et al., 2013; Blackie, 2023). Human – non-human primate conflict is particularly crucial due to primates’ high capacity to live among human populations (Chapman & Chapman, 1990; Alberts & Altmann, 2006; Reader et al., 2011; Sinha & Vijayakrishnan, 2017), and is currently on the rise due to increasing contact between human and non-human primates (Hockings, 2016; Uddin et al., 2020). To characterize and analyze techniques currently being used to …

A Conceptual Approach To Predicting Seismic Events And Flood Risks Using Convolutional Neural Networks, Mahmoud Rehan, Wan-Noorshahida Mohd-Isa, Noramiza Hashim

Journal of Informatics and Web Engineering

This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historical data limits. Traditional risk assessment methods often struggle to estimate such extremes, highlighting the need for more advanced predictive models capable of handling rare but high-impact events. This research enhances CNN architecture to improve accuracy in high quantile predictions by integrating multi-source spatiotemporal data, addressing a critical research gap. The methodology involves incorporating diverse datasets, including geospatial, meteorological, and historical seismic or flood records, into CNN models to augment …

A Spatial Analysis Of Residential Photovoltaic Adoption In New Jersey: Focusing On 2020 With Trends Through 2025, Brandon Mcalister

Geography and the Environment: Graduate Student Capstones

This capstone project seeks to find the relationship between socioeconomic and demographic variables and their relationship to residential photovoltaic installations across New Jersey. The study consists of Geographic Weighted Regression Analyses to construct and socioeconomic index indicating the likelihood of photovoltaic adoption in New Jersey zip codes. Then using the index to predict future photovoltaic adoption across the state. The study found that socioeconomic and demographic variables can predict photovoltaic adoption within one year, but when placed in an index and used to predict future adoption trends, the model under predicts and extremely over predicts. While socioeconomic status is a …

Utilizing Spatial Criteria To High-Grade Wyoming Eor Opportunities Along Proposed Pipeline Corridors: A Value Driven Approach, Jack Borski

Geography and the Environment: Graduate Student Capstones

Oil and gas development has played a critical role in human civilization, and continues to bring drive economies around the world. One such economy is the state of Wyoming that has seen oil and gas production generally decline of the last several decades due to the depletion of high volume conventional reservoirs. A proven secondary technique such as CO2 enhanced oil recovery (EOR) may serve as a method to arrest declining production, and increase economic activity. Wyoming has recognized this opportunity, and has attempted decrease the barriers of entry for oil and gas operators to invest in field-level CO2 EOR …

Object-Based Image Analysis And Artificial Intelligence Identification Of Anthropogenic Disturbance On Lesser Prairie Chicken Habitat In Cheyenne County, Colorado, Tara Hoelzer

Geography and the Environment: Graduate Student Capstones

Renewable energy projects often require extensive landcover for their operations. When one of these projects encroaches into territory of threatened species, such as Lesser Prairie Chickens, an analysis of habitat suitability and human disturbance is required to proceed. Traditionally, this involved manually reviewing aerial imagery within a 6-mile radius, digitizing features, and interpreting them using a human technician—an approach that was time-consuming and prone to human error. By using pretrained AI models within Model Builder™, the identification of roads and structures was automated, making the process faster and more consistent than manual visual analysis. As AI and technology continue to …

Toward Sustainable Human Well-Being: A Multidimensional Assessment In Colorado, Uma Umut Baysal

Electronic Theses and Dissertations

Evaluating progress in human well-being is essential for guiding effective policy and promoting sustainable development. Traditional approaches often emphasize economic and social dimensions while overlooking ecological indicators critical to long-term sustainability. This research addresses that gap by proposing a layered, scalable local framework for county-level analysis and bottom-up decision-making, integrating multiple objective indicators to assess and compare well-being outcomes across regions.

The first goal of this dissertation is to measure human well-being in Colorado counties by developing a Human Well-Being Index (HWBI). This index combines a newly developed Built Environment Index (BEI) comprising five sub-indices: accessibility, housing affordability, transportation, …

A Spatial Modeling Framework For Identifying Multidimensional Risk Factors Of Colorectal Cancer, Johnna K. Berryhill

Student Theses and Dissertations

Colorectal cancer (CRC) is one of the most common and preventable cancers, yet significant disparities in screening, incidence, and late-stage diagnosis persist across different geographic and socioeconomic contexts. This thesis presents a spatial modeling framework for identifying multidimensional risk factors associated with CRC outcomes across various geographic scales. Using county- and census-tract-level data from national and state sources, the study integrates demographic, socioeconomic, environmental, built environment, and behavioral predictors to analyze geographic variability in CRC risk factors. Advanced spatial modeling techniques, including Geographically Weighted Regression (GWR) and Geographically Weighted Random Forest (GW-RF), are employed to capture spatial heterogeneity in these …

Influence Of Tropical Cyclones, Southwest Monsoon, And Tropical Cyclone-Enhanced Southwest Monsoon On Rainfall Variability Over The Western Coast Of The Philippines, Alwin Bathan, Lyndon Mark Olaguera, Faye Abigail T. Cruz, Jose Ramon T. Villarin, Joel T. Maquiling, Maria Obiminda L. Cambaliza, John A. Manalo, Jun Matsumoto

SOSE Affiliate: Manila Observatory

This study investigates the processes driving interannual variability of rainfall over the western coast of the Philippines during the peak southwest monsoon (SWM) months (July–September) from 1961 to 2022. Specifically, it describes how tropical cyclones (TC), SWM, and TC-enhanced SWM influence SWM rainfall variability. Rainfall measurements from 11 stations along the western coast of the Philippines were classified into three types: direct TC rainfall (PD), indirect TC rainfall (PI), and SWM rainfall (PSM). The yearly contributions of PD, PI, and PSM to SWM rainfall were estimated to be 15.4 %, 33.1 %, and 51.5 %, respectively. Furthermore, four rainfall variability …

Virtual Reality’S Impact On Tourist Attitudes In Islamic Religious Tourism: Exploring Emotional Attachment And Vr Presence, Eman Alkhalifah, Ramy Hammady, Mahmoud Abdelrahman, Alyaa Darwish, Ella Cranmer, Ons Al-Shamaileh, Aikaterini Bourazeri, Timothy Jung

All Works

This study explores the integration of immersive technologies, specifically virtual reality (VR), to enhance tourist experiences in the rapidly expanding religious tourism sector. Despite VR’s potential, limited research has examined its impact on religious tourism. This study addresses this gap by investigating the role of emotional attachment in influencing VR presence during pre-, on-site, and postexperiences of VR-mediated religious tourism. A quantitative survey was conducted with 201 respondents who participated in VR religious tourism activities. The empirical analysis, conducted using SPSS and AMOS structural equation modeling (SEM), assessed how VR-mediated religious tourism impacts VR presence and tourist attitudes before actual …

Tellings Of The Pacific Ocean: A Landscape-Based Approach For Multispecies Design And Hci, Maliheh Ghajargar

Engineering Faculty Articles and Research

Environmental disturbances induced by climate change have caused significant changes in our ecosystems and are threatening the health of our environments. As a response to this issue, a growing body of work has emerged in HCI and design, which seeks to foreground more-than-human stories in support of making more sustainable and just futures. This research contributes to this broad agenda by probing graphic novels as a multispecies storytelling method for design and HCI. Combining ideas from Anna Tsing’s adventures of landscape and from HCI and design’s use of sequential art (e.g., storyboards), we use landscape as the main protagonist of …

Ai-Driven Personalized Radiotherapy Planning, Nithin Venkatesh, Marco Pota, Maged Shaban

SAML-25 Workshop on Statistical and Machine Learning

The planning of radiation oncology treatment is made more dynamic and individualized by Artificial Intelligence (AI). Routine radiotherapy practice applies normative procedures indifferent to patient-specific parameters such as tumor volume, patient anatomy, and heterogeneity in the delineation of treatment response. Inadequate and over-radiation treatment is the most prevalent outcome. Further, with the inclusion of AI, it can facilitate enhancing the healthcare industry through optimizing radiotherapy using an array of patient information such as molecular profiles and imaging data. The product offers an end-to-end AI-driven solution to all aspects of radiotherapy, from initial consultation (diagnosis) to adaptive treatment planning. All the …

Convergence Research For Microplastic Pollution At The Watershed Scale, Heejun Chang, Elise Granek, Amanda Gannon, Jordyn M. Wolfand, Janice Brahney

Watershed Sciences Faculty Publications

Microplastics are found in Earth's atmosphere, lithosphere, hydrosphere, pedosphere, and ecosphere. While there is a growing interest and need to solve this grand challenge in both the academic and policy realms, few have engaged with academics, policymakers, and community partners to co-identify the problem, co-design research, and co-produce knowledge in tackling this issue. Using a convergence research framework, we investigated the perception of microplastic pollution among different end users, delivered educational materials to K-12 teachers and practitioners, and identified key sampling points for assessing environmental microplastic concentrations in the Columbia River Basin, United States. Three community partner workshops identified regional …

Arts-Based Sustainability: From New York To Malawi, Martha B. Lerski

Publications and Research

Recognizing that libraries serve multiple constituencies and subject areas, this chapter documents and advocates for development of transdisciplinary arts-based research (ABR) and culture-related projects linked to environmental challenges. Libraries contribute collections and spaces, as well as the research of library and information scientists. Libraries are currently among invisible contributors to sustainability planning and services. The chapter will link this invisibility to the value of what visual arts refer to as negative space elements in subjects ranging from traditional ecological knowledge to environmental science. Library collections, projects, and research contribute to education for sustainable development (ESD) as required to achieve the …

Short Communication: Multiscale Topographic Complexity Analysis With Pytopocomplexity, L. S.-H. Lai, Adam Booth, A. R. Duvall, E. Herzig

Geology Faculty Publications and Presentations

TopoComplexity is a Python package designed for efficient and customizable quantification of topographic complexity using four advanced methods: two-dimensional continuous wavelet transform analysis, fractal dimension estimation, rugosity index, and terrain position index calculations. This package addresses the lack of open-source software for these advanced terrain analysis techniques essential for modern geomorphology and geohazard research, enhancing data comparison and reproducibility. By assessing topographic complexity across multiple spatial scales, pyTopoComplexity allows users to identify characteristic morphological scales of studied landforms. The software repository also includes a Jupyter Notebook that integrates components from the surface-process modeling platform Landlab (Hobley et al., 2017), facilitating …

Toward Integrated Urban Observatories: Synthesizing Remote And Social Sensing In Urban Science, Danlin Yu

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Urbanization is reshaping landscapes and posing unprecedented sustainability challenges, necessitating more integrative approaches to urban observation. This review synthesizes recent advancements in traditional remote sensing and emerging social sensing technologies, emphasizing their convergence within urban science. A systematic thematic analysis of 667 peer-reviewed articles highlights the methodological progress, practical applications, and theoretical innovations arising from this integration. Traditional remote sensing effectively captures urban physical features but lacks insights into human behaviors. Conversely, social sensing, leveraging digital traces from social media and mobile data, introduces essential human-centered dimensions into urban monitoring. The fusion of these complementary paradigms through advanced data analytics …

Glacial Lakes Segmentation Using Multispectral Remote Sensing Data And Deep Learning Models, Debankan Das

Master’s Dissertations

The identification and delineation of glacial lakes through segmentation is crucial for tracking glacial changes and evaluating potential dangers from sudden flood events (GLOFs). These floods can severely impact populated areas and man-made structures downstream. Recent advances in high-quality satellite imagery have sparked increased attention toward using advanced machine learning methods, particularly deep learning, to enable precise and automated glacial lake detection. In this study, we explore the effectiveness of deep learning-based pointwise semantic segmentation for glacial lake mapping using multisource remote sensing imagery, including both optical and synthetic aperture radar (SAR) data. We experiment with a novel stack combination …