Geography Commons^™

Stages Of Being Foreign As Portrayed In Daughter Of Keltoum And Lost Birds, Fran Hassencahl

Communication & Theatre Arts Faculty Publications

In this paper, I use the intercultural communication model, The Stages of Being Foreign, developed by anthropologist Oberg (1960) and modified by Gullahorn & Gullahorn (1963), Lewis & Jungman (1986), and Ward, Bochner, and Furnham (2001) to explain the experience of culture shock. This model describes the stages that individuals experience when they leave, either voluntarily or involuntarily, their home country/culture and must adapt to a new culture. These stages as described by Oberg are a preliminary stage (a spectator stage), an increasing participation stage, the pit of the culture shock stage, the adaptation stage, and for some migrants a …

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Beyond Discrete Indicators: Modeling Intersectional Flood Vulnerability, Sina Razzaghi Asl, Eric Tate, Christopher T. Emrich, Md Asif Rahman, Kaeleb Royster

Political Science & Geography Faculty Publications

Social vulnerability to flooding is shaped by intersectional social marginalization, yet most quantitative assessments employ indicators of single populations. This study applies spatial machine learning to examine how the intersectional social vulnerability indicators of poverty-race, poverty-housing tenure, and race-housing tenure compare with traditional discrete indicators of single populations in predicting flood exposure in California. Using geographically weighted random forests and partial dependence plots, we model spatial heterogeneity and non-linear relationships between social vulnerability and exposure. We quantified flood exposure using a population-adjusted measure derived from building footprints and modeled 500-year fluvial and pluvial flood hazard. The results reveal distinct explanatory …

Regional Oceanographic Controls On Water Column Nitrogen Fixation In Northern Australian Waters, Douglas G. Capone, Ajit Subramaniam, Yubin Raut, Joseph P. Montoya, Margaret R. Mulholland, Rachel Ann Foster, Miles Furnas, Edward J. Carpenter

OES Faculty Publications

Large blooms of the diazotrophic cyanobacteria, Trichodesmium, have been re-ported along the north coast of Australia and are readily evident in remote sensing images. During a research cruise in November 1999, we sampled from Townsville to Broome, examined Trichodesmium population densities and their rates of carbon and N₂ fixation alongside microscopy-based cell counts of them and other cyanobacte-rial diazotrophs. Additionally, we also enumerated the picophytoplankton community using flow-cytometry, measured bulk chlorophyll concentrations, carbon and N₂ fixation rates, and water column hydrography, enabling comparison of diazotrophic and picophytoplankton functional groups across the system. Agglomerative hierarchical clustering analysis of physicochemical oceanographic …

Predicting Cardiovascular Mortality In Hampton Roads Using Social Determinants Of Health, Mohan D. Pant, Aditya Chakraborty, Prachi P. Chavan, George Mcleod, Brett J. Sierra, Glenn A. Yap, Brian C. Martin, Ebbie Kalan, Gregory T. Scott

Cardiovascular Research Symposium

Background: In Virginia’s Hampton Roads (HR) region, minority populations experience notably higher mortality rates than white populations. Despite abundant research on the association between social determinants of health (SDOH) and cardiovascular mortality rates at the state and national levels, there is a lack of research examining this association in the HR region.

Objective: The main objective of this study is to train and validate a geospatial-temporal predictive model to examine the association between SDOH and cardiovascular mortality, in the HR region.

Methods: Utilizing a longitudinal dataset (2010–2021) from the Virginia Department of Health and the U.S. Census Bureau, we trained …

Reproductive Redlining: Unraveling Historical Disparities And Facility Placement In Distance To Licensed Childcare Facilities, Reproductive Health Clinics, & Crisis Pregnancy Centers For Women In The Southern Region Of The United States, Mackenzie A. Kibler

Sociology & Criminal Justice Theses & Dissertations

This dissertation investigates how historical and structural inequalities shape contemporary access to reproductive health services, licensed childcare facilities, and crisis pregnancy centers across Mississippi, Virginia, and Maryland. Using feminist geography, reproductive justice theory, and historical trauma theory, this research develops the concept of reproductive redlining to explore how race, policy, and space intersect to produce health disparities. By combining GIS mapping with multivariate statistical analysis and redlining data from the Home Owners’ Loan Corporation (HOLC), the study evaluates spatial distributions and demographic correlates of facility access before and after the Dobbs decision. Findings reveal enduring spatial inequities that disproportionately impact …

Restored Wetlands Show Rapid Vegetation Recovery And Substantial Surface-Water Expansion, Thilina D. Surasinghe, Yin-Hsuen Chen, Kunwar K. Singh

Center for Geospatial Science, Education & Analytics Faculty Publications

Ecological restoration is essential for improving the ecological integrity of degraded ecosystems to enhance ecosystem services and biodiversity. In this study, we assessed the effectiveness of wetland restoration on retired cranberry farms by analyzing vegetation recovery and surface-water dynamics using the enhanced vegetation index (EVI) and normalized difference water index (NDWI) derived from Sentinel-2 satellite imagery. To quantify temporal dynamics of both vegetation recovery and surface-water cover, we identified the spectral distinctions among restored wetland plant communities. Our results indicated the emergence of distinct plant communities upon restoration. Restored wetlands in general showed significant and progressive vegetation recovery and expanding …

Impact Of Geography On Institutions In Agricultural And Nomadic Societies, Haiwen Zhou

Economics Faculty Publications

How geography affects the choice of institutions is studied in a theoretical model. In this model, nations are located around a circle. Rulers compete through choosing tax rates, the level of military spending, and the degree of formality of institutions. Geographic condition is captured by population density. It is shown that societies with higher population densities choose lower tax rates, establish more formal institutions, and give government officials lower levels of autonomies than those with lower population densities do. A higher level of external threats induces a ruler to choose a higher level of autonomy for officials. The model is …

High-Resolution Modeling Of Extreme Heat Events With Socioeconomic Consideration: A Real-Case Wrf-Les Approach, Maryam Golbazi, Frank Liu, Yin-Hsuen Chen, Timothy W. Juliano, Heather Richter

ODU Articles

The overarching goals of this work is to explore best practices for micro-scale modeling of a real case, identify relevant phenomena by using high-resolution modeling, and to explore their implications for public health, and climate resilience strategies in Hampton Roads, VA, USA. This project employs the Weather Research and Forecasting (WRF) model to conduct a comprehensive study of Hampton Roads, utilizing a coupled mesoscale to microscale modeling capable of resolving boundary layer turbulence. This study has three primary objectives: (1) to establish the optimal mesoscale to Large-Eddy Simulation (LES) configurations for complex geographical regions such as the Hampton Roads (HR) …

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Cities, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

VMASC Publications

An important challenge with Machine Learning (ML) is its transferability; i.e., whether a ML model trained on one set of data can be applied to a second set of data without requiring full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained for one …

Atmospheric Chemistry Experiment (Ace) Winds, Matthew Wyatt, Peter F. Bernath, Chris Boone, Léo Lavy, Ryan Johnson

Chemistry & Biochemistry Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic North are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a ±15 m/s sunrise/sunset shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from the MERRA-2, HWM14, and WACCM-X models. A ±15 m/s …

Social Susceptibility-Driven Longitudinal Tornado Reconnaissance Methodology: 2021 Midwest Quad-State Tornado Outbreak, John W. Van De Lindt, Wanting "Lisa" Wang, Blythe Johnston, P. Shane Crawford, Guirong Yan, Thang Dao, Trung Do, Katie Skakel, Mojtaba Harati, Tu Nguyen, Robinson Umeike, Silvana Croope

Civil & Environmental Engineering Faculty Publications

With the impact of climate change, the intensity and frequency of tornado events have been increasing. Enhancing tornado reconnaissance methods can comprehensively capture building damage and recovery data following tornado events and outbreaks, thereby strengthening community resilience against the threat of future tornado events. Advancements in tornado data reconnaissance research have embraced remote sensing techniques to assess building damage after tornado events, supplanting traditional reconnaissance methods relying on handheld cameras with GIS mapping. Community resilience research offers a groundbreaking perspective, stressing the importance of assessing buildings throughout their recovery cycle-from damage and functionality to recovery-and considering their socioeconomic stability in …

Analysis Of Aerosols In The Asian Monsoon Anticyclone As Observed By The Atmospheric Chemistry Experiment, M. Lecours, R. Dodangodage, C. D. Boone, P. F. Bernath

Chemistry & Biochemistry Faculty Publications

During the Asian summer monsoon season, pollutants from the lower troposphere are transported through deep convection to the upper troposphere and lower stratosphere. Surface pollutants such as CO are transported upward and trapped in the anticyclone during this unique atmospheric phenomenon. Associated with the anticyclone is a layer of enhanced aerosols located near the tropopause often referred to as the Asian tropopause aerosol layer (ATAL). The chemical and physical properties of aerosols in the ATAL are not yet fully understood as direct observations of the aerosols are limited. The Atmospheric Chemistry Experiment (ACE) is a satellite mission that provides high-resolution …

Ensemble Machine Learning Approaches For Bathymetry Estimation In Multi-Spectral Images, Kazi A. Islam, Omar Abdul-Hassan, Hongfang Zhang, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

OES Faculty Publications

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs …

Atmospheric Chemistry Experiment (Ace) V.5.3 Winds: Validation And Model Comparisons, Matthew Wyatt, Peter F. Bernath, Chris Boone, Leo Lavy, Ryan Johnson

Physics Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic north are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a -15 m s^-¹ (+15 m s^-¹) sunrise (sunset) shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from …

High Antarctic Coastal Productivity In Polynyas Revealed By Considering Remote Sensing Ice-Adjacency Effects, Hilde Oliver, Jessica S. Turner, Alexandre Castagna, Henry Houskeeper, Heidi Dierssen

OES Faculty Publications

Ocean color-based estimates of Antarctic net primary productivity (NPP) have indicated low nearshore productivity in ice-adjacent waters, contrasting with coupled physical–biogeochemical models. To understand this discrepancy, we assessed satellite records of polynya NPP by comparing field data with two satellite imagery datasets derived using different processing schemes. Our results indicate historical underestimation of chlorophyll a for imagery obtained using default atmospheric correction processing within approximately 100 km of ice-covered coastlines due to adjacency effects. Using radiative transfer modeling, we find that biases in ocean color polynya observations due to adjacency effects correspond to the high albedo of ice and snow. …

Land Target Detection Algorithm In Remote Sensing Images Based On Deep Learning, Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

Electrical & Computer Engineering Faculty Publications

Remote sensing technology plays a crucial role across various sectors, such as meteorological monitoring, city planning, and natural resource exploration. A critical aspect of remote sensing image analysis is land target detection, which involves identifying and classifying land-based objects within satellite or aerial imagery. However, despite advancements in both traditional detection methods and deep-learning-based approaches, detecting land targets remains challenging, especially when dealing with small and rotated objects that are difficult to distinguish. To address these challenges, this study introduces an enhanced model, YOLOv5s-CACSD, which builds upon the YOLOv5s framework. Our model integrates the channel attention (CA) mechanism, CARAFE, and …

Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang

Electrical & Computer Engineering Theses & Dissertations

The ubiquity of the Global Positioning System (GPS) has cemented its role as the cornerstone for an array of location-based services and navigation systems, spanning applications from autonomous vehicles and drones to maritime vessels and wearable technology. Nonetheless, ensuring the integrity of reported geographical coordinates poses a formidable challenge, owing to the proliferation of diverse GPS spoofing tools. This predicament is compounded by the pervasive availability of tools like Fake GPS, Lockito, and software-defined radios, enabling even unsophisticated users to commandeer and disseminate counterfeit GPS coordinates. This dissertation undertakes the task of devising an encompassing and resilient framework, integrating a …

A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic

Electrical & Computer Engineering Faculty Publications

This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

A Comparative Study Of Vinti-Based Orbit Propagation And Estimation For Cubesats In Very Low Earth Orbits, Ethan Michael Senecal

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, there has been a growing interest in CubeSats and very low Earth orbit (VLEO) space missions. Mission SeaLion, a collaborative CubeSat mission between Old Dominion University, the U.S. Coast Guard Academy, and U.S. Air Force Institute of Technology, planned to launch a 3U CubeSat into VLEO. The VLEO mission is a particularly challenging environment for navigation and orbit propagation because drag introduces a significant perturbation for orbit models such as SGP4. Additionally, mission requirements left no capacity for attitude determination or control, further reducing knowledge of drag behavior of the satellite in flight. This deficiency is a …

Modeling The Impacts Of Sea Level Rise In Coastal Virginia At Multiple Scales, George Murray Mcleod Iv

OES Theses and Dissertations

Relative sea level is increasing along the Mid-Atlantic coast of the United States and the rate of relative sea level rise (ΔRSL) for Coastal Virginia is approximately double the rate of global sea level rise (ΔSLRG)(1). The potential impacts posed to communities by ΔRSL are best understood by examining the spatial relationship between the upper limits of ocean-connected waters and the geographic positioning of critical natural and societal assets. This research examines this problem at three spatial scales to quantify the impacts of ΔRSL and storm flooding events on (i) structural and transportation infrastructure for the tide-influenced coastal zone of …

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

Advancing Estuarine Shoreline Change Analysis Using Small Uncrewed Autonomous Systems, Thomas R. Allen, Devon Eulie, Mariko Polk, George Mcleod, Robert Stuart, Alexandra Garnand, A. J. Manning (Editor)

Political Science & Geography Faculty Publications

Estuarine shorelines face the threats of accelerating sea-level rise, recurrent storms, and disruptions of natural sediment and ecological adjustments owing to historic human interventions. The growing availability and technical capability of uncrewed systems (UxS), including remote or autonomous aerial and surface vessels, provide new opportunities to study and understand estuarine shoreline changes. This chapter assesses the state of the technology, interdisciplinary science and engineering literature, and presents case studies from the Chesapeake Bay, Virginia, and coastal North Carolina, USA, that demonstrate new insights into coastal geomorphic processes and applications to managing complex and dynamic estuarine shorelines. These technologies enhance the …

Impact Of Atmospheric Correction On Classification And Quantification Of Seagrass Density From Worldview-2 Imagery, Victoria J. Hill, Richard C. Zimmerman, Paul Bissett, David Kohler, Blake Schaeffer, Megan Coffer, Jiang Li, Kazi Aminul Islam

OES Faculty Publications

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGC_seagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (L_w), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line …

Participatory Mapping To Address Neighborhood Level Data Deficiencies For Food Security Assessment In Southeastern Virginia, Usa, Nicole S. Hutton, George Mcleod, Thomas R. Allen, Christopher Davis, Alexander Garnand, Heather Richter, Prachi P. Chaven, Leslie Hoglund, Jill Comess, Matthew Herman, Brian Martin, Cynthia Romero

Political Science & Geography Faculty Publications

Background: Food is not equitably available. Deficiencies and generalizations limit national datasets, food security assessments, and interventions. Additional neighborhood level studies are needed to develop a scalable and transferable process to complement national and internationally comparative data sets with timely, granular, nuanced data. Participatory geographic information systems (PGIS) offer a means to address these issues by digitizing local knowledge.

Methods: The objectives of this study were two-fold: (i) identify granular locations missing from food source and risk datasets and (ii) examine the relation between the spatial, socio-economic, and agency contributors to food security. Twenty-nine subject matter experts from three cities …

Hydrological Drought Forecasting Using A Deep Transformer Model, Amobichukwu C. Amanambu, Joann Mossa, Yin-Hsuen Chen

University Administration Publications

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were …

Odu Researchers Attempt To Forecast Flood Impacts In Real Dollars, News @ Odu

News Items

No abstract provided.

A Raft To Coastal Resilience: Odu Researchers Collaborate To Help Rural Communities Combat Flooding Impacts, News @ Odu

News Items

No abstract provided.

Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny

Civil & Environmental Engineering Theses & Dissertations

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for …

Site Selection For Norfolk Day Services Facility, Faith N. Witkowski, Hua Liu

College of Arts and Letters Posters

In October 2021, The Center: A Temporary Shelter transitioned from its downtown location to a residential area a few blocks away. After the move, a pressing, geographic-based question has surfaced: what makes the best location for the houseless population to be able to utilize resources? Using two methods, this study endeavored to answer this question in multiple ways, through different lenses. Method one's objectives are to find an optimal location(s) for a potential Norfolk day service facility based on 1) proximity to social and health services, 2) proximity to a neighborhood that would most benefit from a day center, and …