Geographic Information Sciences Commons^™

Geo-Ai For Wetland Classification And Evolutionary Analysis, Lirong Yin

LSU Doctoral Dissertations

Wetlands, as a crucial component of the Earth's ecosystem, play a vital role in maintaining ecological balance and preserving biodiversity. However, wetlands are currently facing severe challenges, as both natural and human-induced factors are contributing to their global degradation. Gaining a deep understanding of the species composition and biodiversity within wetland-covered areas and accurately analyzing their changing trends not only helps assess the current and future state of wetlands but also provides strong support for the formulation of scientifically sound wetland conservation strategies. In recent years, the rapid development of geospatial intelligence and remote sensing technologies has brought new opportunities …

Sexual Abuse: A Multi-Faceted Problem, Marcus Venable

LSU Doctoral Dissertations

On average, US citizens have experienced approximately 400,000 sexual assaults per year, which results in enormous immediate and long-term consequences for individuals, as well as society in general.

In the U.S., the principal method of combatting this crime has been the creation of Sex Offender Registries used to notify the public of the identity and location of convicted sex offenders who may be living in proximity to their residence. In addition to the Registry, laws have been passed forbidding convicted sex offenders from residing within buffer zones around areas of high child concentration [schools/parks/etc.].

The efficacy and consequences of these …

Spatial Behavior Of Hospital Visits By Hand, Foot, And Mouth Disease Patients In Nanchang, China, Zeliu Zheng

LSU Doctoral Dissertations

Hand foot mouth disease (HFMD) is one of the widespread transmissible diseases that target preschool children, especially in urban regions in East Asia. Understanding the travel patterns of the HFMD patients helps us understand how the spatial behaviors of patients vary across space and what are the underlying forces. It is essential for understanding the healthcare market and planning for resource allocation. Foremost, health behavior and outcome change significantly across geographic regions of various urbanicities (i.e., degrees of urbanization) due to the uneven distribution of healthcare resource. In addition, health studies in the U.S. often use hospital service areas (HSAs) …

Effects Of Social Media Use Disparities On Community Resilience To Disasters, Kejin Wang

LSU Doctoral Dissertations

With the rapid development of social media, many researchers chose to use social media data to conduct studies of disaster resilience. This dissertation addresses three fundamental challenges related to social media use and disaster resilience analysis including: how the spatial analysis scale affects the results of social media use disparity and its impacts on disaster resilience; how different vulnerability and resilience measurement methods can generate very different results; and how social media use disparity can be identified to help improve the fairness of AI-based emergency rescue model development. Therefore, the first part of the dissertation measured the relationships between disparities …

Communicating Nature-Society Relationships In Coastal Louisiana: An Evaluation Of The Ecosystem Services Framework, Vanessa Van Heerden

LSU Doctoral Dissertations

The ecosystem services (ES) framework is a tool to communicate the value of natural environments to human well-being by monetizing services that natural environments provide to humans. The Louisiana Coastal Master Plan uses the ecosystem services provided by the Mississippi River Delta as rationale for why coastal Louisiana should be protected. Here, I am interested in determining how the ecosystem services framework is used to communicate nature-society relationships in coastal Louisiana. I conducted a meta-analysis and spatial analysis to understand the spatial relationships of ecosystem services in the wetlands of coastal Louisiana. I then conducted a survey of residents of …

Mapping, Modeling, And Predicting Extreme Flood Events With Cloud Computing, Dan Tian

LSU Doctoral Dissertations

Floods represent one of the most severe natural disasters worldwide. It is crucial to accurately assess flood hazards to mitigate the impact and enhance community resilience. This study focuses on three key components of flood hazard management, including (1) flood frequency estimation, (2) inundation delineation, and (3) flood susceptibility assessment. The first project presents a Bayesian Log-Pearson Type III model with Spatial Priors (BLP3-SP) that utilizes spatial regression priors to enhance the accuracy of flood frequency estimation for sites with limited data. The method is compared with two other algorithms with different priors. The results indicate that BLP3-SP performs the …

A Subspecies-Level Database Of Amazonian Bird Distributions, With Inferences On Suture Zones And Conservation, Marco Antonio Rego

LSU Doctoral Dissertations

Amazonia has the largest and most biodiverse tropical forest on the planet. However, the distributions of its species are still poorly understood, even for well-studied vertebrates such as birds. Available distribution maps for Amazonian birds often lack accuracy in delimiting the area where species occur. Existing distributional information for Amazonian birds is often limited to species-level level taxonomy, even though many Amazonian bird subspecies represent biological species. Here, I investigate the geographic distributions of 4,148 bird taxa (species and subspecies) using museum scientific specimens as the primary source of data. To build the data base I use more than 600,000 …

Estimation Of Economic Risk From Coastal Natural Hazards In Louisiana, Rubayet Bin Mostafiz

LSU Doctoral Dissertations

Louisiana, U.S.A., is among the most vulnerable areas globally to coastal natural hazards, with risk vulnerability likely increasing. The risks associated with non-tropical-cyclone hazards in Louisiana’s coastal zone have been understudied. This research enhances present and future (i.e., 2050) Louisiana risk assessment using locally-weighted, model-based hazard frequency/intensity and population projections.

Results suggest that property risks associated with extreme cold temperature and tornado are and will remain costlier than those for hail and lightning. Property risks of extreme cold temperature and hail are projected to decrease with the expected warming temperatures, with those of all four of these hazards peaking in …

Gis Automated Delineation And Analysis Of Cancer Service Areas In The United States, Changzhen Wang

LSU Doctoral Dissertations

Delineating a meaningful and reliable geographic unit pertaining to cancer care is essential in examining geographic variations in cancer care for better analysis, management, and planning. Public health researchers have devoted great efforts to defining various service areas, which; however, lack scientific rigor or are unrepresentative of the highly specialized cancer care markets, and their methods have become obsolete in the era of big data and high geo-computation. This study develops the “Spatially Constrained Leiden (ScLeiden)” method, a network community detection algorithm in Geographic Information Systems (GIS), and applies it to delineate a series of coherent cancer service …

A Street-Based Simulation Approach To Evaluating Crime Theories And Deterrence Efficacy In Baton Rouge, Louisiana, Shaun Edward Williams

LSU Doctoral Dissertations

Criminology of place and deterrence strategy evaluations share separate yet similar paths towards incorporating microgeographic units of analysis within deterrence strategies. These transitions have been underway since Weisburd’s 2015 criminology of place work and Kennedy’s 1997 Ceasefire publication for deterrence strategy evaluation. Rather than purely theoretical or practical challenges serving as agents of change, scale appropriateness can arguably be pinpointed as the foundation for change in both areas. Microplace offers improved insight into the study of crime and place dominated by areal designs. This status quo has hampered evaluation but has not slowed the flow of resources to support strategy …

Using Spatial Analysis And Machine Learning Techniques To Develop A Comprehensive Highway-Rail Grade Crossing Consolidation Model, Samira Soleimani

LSU Doctoral Dissertations

The safety of highway-railroad grade crossings (HRGC) is still an issue in the United States of America (USA). The grade crossing is where a railroad crosses a road at the same level without any over or underpass. To improve the safety of crossings, the crossings’ condition should be explored from several aspects such as engineering design (speed limit, warning signs, etc.), road condition (number of lanes, surface markings, etc.), rail design (the type of track, ballast, etc.), temporal variables (weather, visibility, time of day, lightning, etc.), social variables (population, race, etc.), and last but not least, spatial variables (the type …

An Atmospheric And Spatiotemporal Examination Of Lightning-Initiated Terrestrial Gamma-Ray Flashes Detected By The Fermi Satellite And Tetra Ii, Deirdre Colleen Smith

LSU Doctoral Dissertations

Terrestrial Gamma-ray Flashes (TGFs) are sub-millisecond bursts of the highest naturally occurring light-energy found within Earth’s atmosphere. TGFs are associated with the electric fields produced in thunderstorms and are geolocated by coincident sferics from lightning strokes. Though billions of lightning strokes occur globally each year, fewer than 1,000 TGFs are detected via satellite and ground-based sensors and only a small fraction are geolocated via sferics.

To date, few studies have focused on individual thunderstorms and climates that produce TGFs. This dissertation examines TGFs from two differing data samples: 1) NASA's Fermi Gamma-Ray Burst Monitor (2013-2018) and 2) The TGF and …

Deciphering Public Transit Ridership In Baton Rouge: Spatial Disaggregation Approaches, Xuan Kuai

LSU Doctoral Dissertations

Background: Surveys across the U.S. reveal that commuters driving personal vehicles spend a significant amount of time in traffic, while public transit, as an efficient commuting mode, has been largely underutilized.

Purpose: What causes a low public transit ridership? How could public transit ridership be explained by demographic, socio-economic and spatial characteristics of neighborhood? This study answers these questions by deciphering the relationships between public transit ridership and various factors in a medium-size city in southern U.S. – Baton Rouge, Louisiana.

Methods: Non-spatial and spatial data in a larger areal unit (e.g., block group) are used to infer demographic, socio-economic …

The Importance Of Landscape Position Information And Elevation Uncertainty For Barrier Island Habitat Mapping And Modeling, Nicholas Matthew Enwright

LSU Doctoral Dissertations

Barrier islands provide important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. As a result, natural resource managers are concerned with monitoring changes to these islands and modeling future states of these environments. Landscape position, such as elevation and distance from shore, influences habitat coverage on barrier islands by regulating exposure to abiotic factors, including waves, tides, and salt spray. Geographers commonly use aerial topographic lidar data for extracting landscape position information. However, researchers rarely consider lidar elevation uncertainty when using automated processes for extracting elevation-dependent habitats from lidar data. …

The Use Of Geospatial Modeling And Novel Diagnostics To Detect And Map Risk Factors Of Soil-Transmitted Helminths In Feira De Santana, Brazil, Ryan Harry Avery

LSU Doctoral Dissertations

Soil-transmitted helminth (STH) infections impact billions of people worldwide. The traditional STH control approach is a morbidity control strategy implementing mass drug administration (MDA) programs targeting school-aged children (SAC). In Brazil, this control strategy has decreased STH prevalence to less than 20% in most of the country and providing an opportunity to transition from the morbidity control program and towards a surveillance and response system geared towards STH elimination. Surveillance and response systems geared towards elimination require the implementation higher accuracy diagnostics to detect infection in low-transmission communities, surveillance of entire households, high-resolution modeling at the household-habitat scale, and targeted …

Vulnerability Of Industrial Facilities In The Lower Mississippi River Industrial Corridor To Relative Sea Level Rise And Tropical Cyclone Storm Surge, Joseph Blake Harris

LSU Doctoral Dissertations

Relative sea level rise (RSLR) and tropical cyclone-induced storm surge are major threats to the Lower Mississippi River Industrial Corridor (LMRIC) which has approximately 120 industrial complexes located within the corridor. Spatial interpolation methods were applied to the 2004 National Oceanic and Atmospheric published Technical Report #50 subsidence dataset and cross-validation techniques were used to determine the accuracy of each method. Digital elevation models (DEMs) were created for the years 2025, 2050, and 2075, based on these predictive surface of subsidence rates. Future DEMs were utilized to model RSLR and determine the extent of storm surge on the LMRIC by …

Using Deep Learning To Forecast Spatiotemporal Crime Patterns, Shuzhan Fan

LSU Doctoral Dissertations

The distributional patterns of crime occurrences are closely related to their spatial, temporal, and environmental contexts. It has been a hot topic for researchers and crime analysts to discover such complex relationships in order to forecast crime, both spatially and temporally. Many factors play a role in the occurrences of crimes. Conventional crime forecasting research has primarily relied on historical crime records and socioeconomic data, while ignoring the rich social media and other environmental context data. The large volume of data requires a more appropriate forecasting framework with the ability to take in massive multimodal data and possibly achieve better …

Gis Analysis Of Dvāravatī Dharmacakras And The Rise Of Buddhism In Thailand, Areerut Patnukao

LSU Doctoral Dissertations

This dissertation explores how GIS as well as spatial and statistical analyses could be used to advance the understanding of Dvāravatī settlement and Dharmacakras locations. The research employs archaeological and geographical parameters to measure and quantify the patterns of Dvāravatī settlements, Dharmacakra locations, their interrelationship, and their relationship with environmental setting. The different types of spatial analyses, parameter settings within each analysis, and approaches are used to examine and explore the differences and commonalities of these variables at three different geographic levels: national, regional, and river basin levels.

Four distinct approaches are incorporated in this study. Chi-Square analysis shows significant …