Spatial Science Commons^™

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 …

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 …

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 …

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 …

Examining Arctic Melt Pond Dynamics Via High Resolution Satellite Imagery, Austin Abbott, Victoria Hill

College of Sciences Posters

The Arctic Ocean is a rapidly changing environment, and a key observational system for monitoring climate change. The Arctic is going under a rapid transition from thicker, multi-year ice, to thinner first-year ice, that may have many potential consequences. As first year Arctic sea ice begins to retreat in the spring and early summer, melting snow and ice form ponds on the surface- “melt ponds”. These melt ponds increase light transmission to the water column, resulting in warming and increased primary production under the ice. Recent advances in high resolution satellite imagery now allow us to monitor the development and …

Exploring Spatial Patterns Of Virginia Tornadoes Using Kernel Density And Space-Time Cube Analysis (1960-2019), Michael J. Allen, Thomas R. Allen, Christopher Davis, George Mcleod, Wolfgang Kainz (Ed.), Dean Kyne (Ed.)

Political Science & Geography Faculty Publications

This study evaluates the spatial-temporal patterns in Virginia tornadoes using the National Weather Service Storm Prediction Center’s Severe Weather GIS (SVRGIS) database. In addition to descriptive statistics, the analysis employs Kernel Density Estimation for spatial pattern analysis and space-time cubes to visualize the spatiotemporal frequency of tornadoes and potential trends. Most of the 726 tornadoes between 1960–2019 occurred in Eastern Virginia, along the Piedmont and Coastal Plain. Consistent with other literature, both the number of tornadoes and the tornado days have increased in Virginia. While 80% of the tornadoes occurred during the warm season, tornadoes did occur during each month …

Scaling Effect Of Fused Aster-Modis Land Surface Temperature In An Urban Environment, Hua Liu, Qihao Weng

Political Science & Geography Faculty Publications

There is limited research in land surface temperatures (LST) simulation using image fusion techniques, especially studies addressing the downscaling effect of LST image fusion. LST simulation and associated downscaling effect can potentially benefit the thermal studies requiring both high spatial and temporal resolutions. This study simulated LSTs based on observed Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) LST imagery with Spatial and Temporal Adaptive Reflectance Fusion Model, and investigated the downscaling effect of LST image fusion at 15, 30, 60, 90, 120, 250, 500, and 1000 m spatial resolutions. The study …

Temporal And Spatiotemporal Investigation Of Tourist Attraction Visit Sentiment On Twitter, Jose J. Padilla, Hamdi Kavak, Christopher J. Lynch, Ross J. Gore, Saikou Y. Diallo

VMASC Publications

In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists' emotions when visiting a city's tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and …

Assessment Of Spatiotemporal Fusion Algorithms For Planet And Worldview Images, Chiman Kwan, Xiaolin Zhu, Feng Gao, Bryan Chou, Daniel Perez, Jinag Li, Yuzhong Shen, Krzysztof Koperski, Giovanni Marchisio

Electrical & Computer Engineering Faculty Publications

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. …

Agenda, Hr Adaptation Forum

January 23, 2015: Storm Surge Modeling Tools for Planning and Response

No abstract provided.

Using Geographically Weighted Regression Models To Analyze Crash Harm, Libin Zheng

Civil & Environmental Engineering Theses & Dissertations

Society pays a high cost for collisions in terms of property damage, injuries and loss of life. This paper has two objectives. One is to examine various factors associated with harm caused by highway collisions. Both global OLS and local GWR models are provided to identify specific variables influencing crash harm. Another objective is to demonstrate the use of a Geographically Weighted Regression (GWR) method in this complex safety problem, which can estimate models for each crash location and show spatial variation. The results show that the GWR model is a significant improvement on the OLS model; the test for …

Modeling Geographic Population Dispersion Utilizing Geospatial Information System Environment Agents In An Agent Based Model, Karl D. Liebert

Computational Modeling & Simulation Engineering Theses & Dissertations

New capabilities in agent based model (ABM) environments are opening the door to the creation of ABM that may incorporate high-quality, real world environment data in the form of Geospatial Information System (GIS) files . In the past, GJS environments were only possible through extensive software development efforts focused on specific model applications.

This thesis explores the value and issues of using GIS data to provide an ABM environment. It examines the ability of ABM development environments (DE) to support GIS environment data. The selected ABM DE is then used to model population behavior in an environment defined by authoritative …

Spatial Analyses And Repletion Of Gargathy Coastal Lagoon, Loreto Herraiz Gomez

OES Theses and Dissertations

Coastal lagoons and bays vary in shape and size in response to antecedent topography, geologic processes and sea level rise. Variations in shape and environmental conditions of coastal basins are believed to influence the distribution of benthic sub-environments and the exchange of water with the ocean and other adjacent coastal systems. Gargathy Inlet and its coastal lagoon vary spatially from the inlet, where the greatest depths are observed, to the mainland, dominated by shallow intertidal areas, colonized by marsh. Hypsographic and hydro-hypsographic analyses of Gargathy's coastal lagoon were the primary techniques applied to understand the relative distribution of the benthic …

Flow Kinematics And Dynamics Of The Gulf Stream From Composite Imagery, Caitlin Patrice Mullen

OES Theses and Dissertations

A unique set of contemporaneous satellite-tracked drifters and five-day composite satellite images of the North Atlantic is studied in order to infer the near-surface flow kinematics and dynamics of the Gulf Stream. Using fractal and spectral analyses, two kinematic models, and a potential vorticity model, detailed comparisons are made between these data sets.

Fractal and spectral analyses show that the data set is not fractal, there is no geographic variability, and there is not a strong fractal scaling link between the drifter trajectories and composite temperature fronts as had been postulated by several investigators. These results indicate considerably more work …