Geography Commons^™

Below The Rows, Beyond The Roots: An Art Exhibition Depicting Agriculture Across The Globe, Maggie Enoch

Honors Theses and Capstones

In Below the Rows, Beyond the Roots, artist Maggie Enoch creates multimedia works inspired by her exposure to diverse agricultural systems and perspectives while studying geography and sustainable agriculture/food systems around the world. By integrating complex histories with the contemporary realities of farming, Maggie paints vivid pictures of the power of food in this five-piece exhibition.

Submesoscale Dynamics Of Phytoplankton And Carbon Export Revealed By High-Resolution Airborne And Satellite Remote Sensing Of Currents And Ocean Color, Sarah E. Lang

Open Access Dissertations

Satellites and airborne sensors reveal submesoscale (1 - 10 km) variability in ocean color in the form of filaments, eddies, and patches. The variability in ocean color is closely tied to the physical dynamics that restructure phytoplankton distributions and drive active biological responses like changes in primary productivity and community structure. As the base of the marine food web and a key component of the biological carbon pump, phytoplankton are crucial to the overall health of marine ecosystems and to the ocean's role in climate. This dissertation focuses on the use of airborne and satellite remote sensing to study the …

Using Remote Sensing Technology To Develop A Framework For Improving Hydrologic Models, Marissa Cook

Theses, Dissertations and Capstones

With increased storm intensity due to climate change and urbanization, flash flooding has become an increasingly significant issue globally and regionally. Although the factors influencing urban flash flooding are well-known, there is a growing need for technology to accurately and remotely predict the chance of a flash flood occurring from any given rain event to give people time to prepare. This study aims to use multispectral satellite imagery to provide a framework for improving near real-time flood predictions in an urban area of a high gradient, fourth order stream impacted by flooding. Specifically, we utilize satellite imagery to create the …

Data-Driven Methodologies For Mapping Cultural Heritage: The Case Of The National Coal Heritage Area, West Virginia, Usa, Hossain Mohammad Nahyan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The objective of this dissertation was to develop a comprehensive, data-driven spatial framework for characterizing the complex cultural landscape of the National Coal Heritage Area (NCHA) in West Virginia. By transitioning away from traditional, heuristic spatial mapping, this research integrates advanced spatial statistics, machine learning, and GIS-based methodologies to objectively quantify the physical, visual, and cultural dimensions of the post-mining environment. The research is structured around three interconnected empirical studies, each addressing a specific scale of the Landscape Character Assessment (LCA) framework to support heritage conservation and sustainable spatial planning. The first paper focused on landform classification, developing an automated …

Spatial Patterns And Morphometric Evolution Of Sinkholes In Response To Watershed Hydrogeomorphology: Examples From A Karst Landscape In The Missouri Ozarks, Usa, Marcell Tóth

Graduate Theses/Dissertations

Sinkholes are characteristic enclosed depressions with internal drainage connecting the surface and subsurface karst hydrologic system. Their morphological evolution involves gradual subsidence of the ground surface and hazardous collapses. Therefore, understanding sinkhole morphometry and linked spatial distribution is critical for managing geohazards in karst watersheds. Sinkhole occurrence shows spatial variability based on watershed geomorphological attributes, surficial hydrological patterns, hydrogeological and geological settings. The aim of this research is to investigate morphometric properties and distribution of sinkholes in the carbonate karst-dominated lands of Mark Twain National Forest in Missouri, USA. The specific objectives were to (1) identify sinkhole clusters based on …

Identifying Mobility Hub Suitability In The Mid-Sized United States Urban Area Using Weighted Overlay And Percentile Based Local Peak Analysis, Eric Asplund

Theses and Dissertations

IDENTIFYING MOBILITY HUB SUITABILITY IN THE MID-SIZED UNITED STATES URBAN AREA USING WEIGHTED OVERLAY AND PERCENTILE‑BASED LOCAL PEAK ANALYSIS

By Eric Asplund

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Urban and Regional Planning at Virginia Commonwealth University.

Virginia Commonwealth University, 2026.

Major Director: Dr. Ivan Suen, Ph. D., Associate Professor, Faculty of Urban and Regional Studies and Planning

Shared mobility hubs are increasingly posited in transportation planning as interventions supporting multimodality, sustainability, and equitable access, but guidance on evaluation of potential hub locations remains uneven, particularly in mid-sized United States cities where …

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 …

A Sustainable & Universal Redesign Of Hickory Hill Park In Richmond, Virginia, Ren Hollis, Cynthia Lin, Kira Miller, Jackson Nivera, Patrick O’Shea, Corinne Tsou, Hayston Wines

Undergraduate Research Posters

Urban green spaces provide essential environmental, psychological, and physical benefits, yet access to these resources is often inequitable. Cities are increasingly vulnerable to climate change, highlighting the need for adaptive design. This study focuses on the redesign of Hickory Hill Park in Southside Richmond, selected through a combination of site suitability analysis and qualitative survey. The guiding research question is: How can a park in Richmond be designed to optimize environmental resilience, accessibility, and community benefits?

The selection of a research location and scope used a mixed-methods approach integrating spatial analysis, environmental assessment, and community engagement. A site suitability analysis …

High-Resolution Mapping Of Soil Moisture Variation Using Uas Thermal And Multispectral Imagery, Jackline Amma Timah

Theses and Dissertations

In agricultural landscapes, soil moisture regulates hydrologic partitioning, nutrient transport and water quality, land-atmosphere energy exchange that shapes local climate, and ecosystem resilience. However, traditional monitoring approaches, such as in-situ sensors and satellite imagery, often lack the spatial resolution required to capture fine-scale soil moisture variability. This study evaluated whether unmanned aerial system (UAS)-derived thermal, multispectral, and terrain variables can capture fine-scale spatial variability in volumetric water content (VWC) within an SRB in central Illinois.

High-resolution imagery was collected and paired with 50 field-measured VWC observations. Land surface temperature (LST), vegetation indices (NDVI and NDRE), spectral bands, and slope were …

Mapping Robusta Coffee (Coffea Canephora) Cropping Systems In Uganda: A Two-Step Pixel And Sub-Pixel Based Approach With Sentinel-2 Data, Getachew Kebede, Bester Tawona Mudereri, Onisimo Mutanga, Tobias Landmann, John Odindi, Natacha Motisi, Fabrice Pinard, Henri E.Z. Tonnang, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

Coffee is a highly valued commodity and a widely consumed beverage, playing an important role in global trade. However, coffee farming landscapes are increasing transitioning into smaller-scale agricultural setups. This transformation highlights the critical need for accurate classification and mapping of coffee cropping systems (CS), especially in countries like Uganda, where dense vegetation and complex terrain present substantial challenges to traditional land survey methods. Moreover, understanding the spatial distribution of Robusta coffee (Coffea canephora) CS is essential for developing site-specific management strategies, guiding extension services, and informing evidence-based policy decisions. To address this gap, the present study aimed to enhance …

Multidimensional Analysis Of Human Outdoor Comfort: Integrating Just-In-Time Adaptive Interventions (Jitais) In Urban Digital Twins, Binyu Lei, Pengyuan Liu, Kunihiko Fujiwara, Mario Frei, Clayton Miller, Xuan Yun Chua, Filip Biljecki

Research Collection College of Integrative Studies

How can bidirectional information exchange be enhanced in urban digital twins, and support human-centric data and processes? Their key characteristic is the nearly real-time exchange of information, allowing adjustments to physical environments based on simulations and analytics within virtual models. Yet, achieving such interaction remains challenging, particularly regarding device deployment and infrastructure development. Embracing the concept of humans as sensors, this work develops a two-way framework based on the emerging concept of just-in-time adaptive interventions (JITAIs), exploring how urban digital twins can play a role in understanding and enhancing human comfort outdoors. Human comfort outdoors is inherently spatio-temporal and personalised, …

Multi-Satellite Image Matching And Deep Learning Segmentation For Detection Of Daytime Sea Fog Using Gk2a Ami And Gk2b Goci-Ii, Jonggu Kang, Hiroyuki Miyazaki, Seung Hee Kim, Menas Kafatos, Daesun Kim, Jinsoo Kim, Yangwon Lee

Institute for ECHO Articles and Research

Traditionally, sea fog detection technologies have relied primarily on in situ observations. However, point-based observations suffer from limitations in extensive monitoring in marine environments due to the scarcity of observation stations and the limited nature of measurement data. Satellites effectively address these issues by covering vast areas and operating across multiple spectral channels, enabling precise detection and monitoring of sea fog. Despite the increasing adoption of deep learning in this field, achieving further improvements in accuracy and reliability necessitates the simultaneous use of multiple satellite datasets rather than relying on a single source. Therefore, this study aims to achieve higher …

Towards Spatial Inversion Of Aerial Gamma-Ray Survey Data For Measurement Of Naturally Occurring Radioactivity, Daniel A. Haber

UNLV Theses, Dissertations, Professional Papers, and Capstones

Aerial gamma-ray surveying (AGRS) is used in geologic and environmental contexts to provide data on the surface spatial distribution of naturally occurring radioactive material (NORM) or other gamma-ray-emitting isotopes. The standard data reduction workflow for AGRS data involves a process whereby pointwise gamma-ray spectral data are denoised, corrected for numerous sources of background radiation and aircraft height, and are finally converted to physical values by empirical conversion factors. The reduced pointwise data are then typically spatially interpolated to form a continuous surface map.

This dissertation introduces and explores a novel spatial inversion method for reduced AGRS data that considers aircraft …

The Chemistry Of Color: A Comparative Analysis Of Natural And Synthetic Dyes In Textile Application, Caitlyn Pinaga Cpht

Honors Program Theses and Research Projects

The Chemistry of Color: A Comparative Analysis of Natural and Synthetic Dyes in Textile Application examines how color functions at the intersection of chemistry, culture, and environmental responsibility. This project traces the evolution of dyeing from ancient natural pigment traditions, rooted in ecological knowledge, agricultural practices, and cultural identity, to the industrial rise of synthetic dyes, whose laboratory precision enabled unprecedented consistency, brightness, and global textile expansion. Through experimental swatch analysis, the study compares the behavior of natural dyes derived from plants and food sources with modern fiber-reactive and synthetic dye classes on a range of fibers including cotton, bamboo …

Evaluating The Preparedness Of Local Zoning Regulations For Flood Risk Reduction In The Most Affected Local Jurisdictions In Nebraska, Md Asaduzzaman Noor

Community and Regional Planning Program: Theses

Flooding has profound social, economic, and environmental impacts on local communities, and zoning plays a critical role in mitigating these risks. The 2019 Nebraska floods, among the most severe in the state’s history, highlighted the urgent need to strengthen local preparedness and mitigation strategies. This study assesses the extent to which local zoning regulations in Nebraska’s most affected jurisdiction, including rural areas, address flood risk reduction. A systematic review of 117 zoning ordinances from counties, cities, towns, and villages, we applied a structured analytical framework encompassing regulatory and permitting policies, voluntary and incentive-based measures, and nature-based solutions. The results show …

Flood Resilience Through Working-Land Conservation: Assessment Of Wetland Inundation Dynamics Across Wrp, Wma, Wpa, Padus And Crp Lands In Nebraska (2018–2024), Pranjay Joshi

Community and Regional Planning Program: Theses

This study first confirms whether Nebraska’s wetlands are still functioning hydrologically in ways that reduce flood impacts. Wetlands are known to lessen flood damage by storing water, slowing runoff, and moderating peak flows, but these benefits depend on the wetlands’ ability to maintain inundation and saturation through time. Many wetlands across the state have undergone drainage, hydrologic alteration, or isolation from surrounding watersheds, raising uncertainty about their present-day functioning. Using seven years of Sentinel-2 imagery processed in Google Earth Engine, this research establishes a clear, long-term record of inundation patterns across thousands of wetland parcels. This analysis verifies which wetlands …

Rainfall-Runoff Modelling In An Indonesian Humid Tropical Area Using Satellite-Based Precipitation Products, Noordiah Helda

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores three rainfall-runoff models in the humid tropical regions of Indonesia using satellite-based precipitation products (SBPPs) and develops integrated machine-learning modeling frameworks. Several ground-based observations from BMKG (Badan Meteorologi, Klimatologi, dan Geofisika (also known as the Indonesian Agency for Meteorology, Climatology, and Geophysics)) stations across Indonesia (133−165 stations) are compared and evaluated against satellite products, indicating that GPM performs well, with R-squared values ranging from 0.54 to 0.76 and correlation coefficients ranging from 0.45 to 0.69, respectively.

In the Martapura Watershed, South Kalimantan, due to a lack of observational discharge data, streamflow was generated using the FJ Mock …

Global, Continental, And Local Scale Paleoenvironmental Reconstruction Methods For Interpreting The History Of Miocene North America And The Great Plains, Willow Hue Nguy

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The Miocene of North America is characterized by dynamic changes in herbivore communities, habitat composition, and global climate. Long-term cooling and drying trends influenced large changes in floral and faunal communities. The Great Plains, North America shifted from closed-canopy biomes to open-canopy biomes with C3-grasses to biomes with C4-grasses. This shift affected the herbivore communities as browsing-adapted ungulates were replaced by grazing-adapted ungulates. Much focus has centered on the Great Plains, so it is not well understood how the changes in biomes compare to other regions of North America. The models used for vegetation density indicate open-canopy biomes since at …

Mountain Communities During A Time Of War: A Case Study Of The Hutsul Region In The Carpathian Mountains Of Ukraine, Pavlo Rybaruk

Electronic Theses and Dissertations

This thesis investigates the ethno-ecological technologies employed by the Hutsul people within the highland agrarian economy of the Carpathian Mountains. Over centuries, the Hutsuls have developed ethno-ecological technologies that maintain ecological integrity while supporting community livelihoods.

The study addresses three primary research questions: What are the most important ethno-ecological technologies of the Hutsul highland economy? How might these traditional ethno-ecological practices be applied to economic, agricultural, and tourism development in the Hutsul region? How might these traditional ethno-ecological practices be combined with contemporary approaches to encourage sustainable development in the region?

The research explores the devastating impact of the Russian …

Modeling Flood Risks For Small-Scale Coastal Watershed Across Shared Socioeconomic Pathway Scenarios, Sebastian Loschner

Graduate Theses and Dissertations (2019 - present)

Coastal flooding, driven by the mixture of natural processes and human activities such as precipitation, waves, sea level rise, and urbanization, remains a growing concern. While recent flood-risk studies use IPCC's Shared Socioeconomic Pathways with climate projections to assess future flood exposure, smaller coastal watersheds, < 120,000 acres, remain insufficiently studied. Projected sea level rise is expected to intensify these impacts in smaller systems, potentially causing more severe flooding than reported for larger watersheds. To address this gap, this study used the SRH-2D model integrated with Aquaveo's Surface-water Modeling System to simulate flooding in the lower Fish River basin, Alabama. A coastal watershed sensitive to both riverine and tidal influences. Simulations tested different sea levels based on SSP scenarios corresponding to low, moderate, and high emissions for the years 2050 and 2100. Results indicate that the midcentury scenarios remained even in inundation extent and volume, between 9.9-10.4% compared to the 2020 baseline, the latter scenarios had a wider range in results of between 25.9-50.3% compared to the same baseline. Across scenarios, the most vulnerable and inundated areas of the smaller coastal watershed were the narrow points where upstream flow convene with downstream backwater. These findings highlight the need for futuristic location-specific flood mitigation strategies.

Detecting Prescribed Fire, Haying And Grazing Events Via Remote Sensing To Create Grassland Disturbance Landcovers For The Ring-Necked Pheasant (Phasianus Colchicus), Megan Amy Baldissara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation developed disturbance detection models to fulfill the need for remote sensing landcover products describing grassland structure. The use of landcover products derived from remote sensing is increasing over time in pheasant (Phasianus colchicus) research. Such landcover, however, does not provide relevant pheasant structural habitat information (Chapter 1). Pheasants require tall, high-density grassland for nesting, tall grassland with medium density for brood rearing, and tall grassland for wintering. Time since disturbance can serve as a proxy for structure, as it shapes vegetation by removing biomass and resetting succession. Disturbance is easier to detect than structure with current …

Pilot-C: Physics-Informed Low-Distortion Optimal Trajectory Compression, Kefei Wu, Baihua Zheng, Weiwei Sun

Research Collection School Of Computing and Information Systems

Location-aware devices continuously generate massive volumes of trajectory data, creating demand for efficient compression. Line simplification is a common solution but typically assumes 2D trajectories and ignores time synchronization and motion continuity. We propose PILOT-C, a novel trajectory compression framework that integrates frequency-domain physics modeling with error-bounded optimization. Unlike existing line simplification methods, PILOT-C supports trajectories in arbitrary dimensions, including 3D, by compressing each spatial axis independently. Evaluated on four real-world datasets, PILOT-C achieves superior performance across multiple dimensions. In terms of compression ratio, PILOT-C outperforms CISED-W, the current state-of-the-art SED-based line simplification algorithm, by an average of 19.2%. For …

Harnessing Hyperspectral Imaging And Deep Learning For Terrestrial Habitat Mapping In Arid Landscapes: A Case Study In Saudi Arabia, Ali Elgendy, Hesham Morgan, Brandon Tran, Rejoice Thomas, Tamer Ismail, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Muburak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arid ecosystems remain under-mapped at actionable scales despite their ecological importance. Decision makers lack reliable, high-resolution habitat maps in drylands to prioritize protection and target restoration. This research integrates spaceborne hyperspectral imaging from the Environmental Mapping and Analysis Program (EnMAP) with deep learning semantic segmentation models to produce an updated level of habitat classification based on the International Union for Conservation of Nature (IUCN) for part of the Imam Turki bin Abdullah Royal Reserve, Saudi Arabia. Using ground control points and the full EnMAP spectral cube without band selection, U-Net and DeepLabV3+ architectures were each implemented with VGG19 and ResNet-101 …

Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm

Electronic Theses and Dissertations

Archaeological Predictive Modeling stands firmly as an important tool for Archaeologists to predict undiscovered sites from civilizations all across the globe. While powerful, this methodology is not without its own set of qualms. Striking a balance between pure a data-driven approach while also observing leading expert theories can be a complicated task. Going further, deciding on the specific domain of features to emphasize or overlook can be a challenge within itself, as one misstep can drastically change the output of model, sometimes for the worst. In addition, creating models that can expose their reasoning process can be rather difficult to …

Shape: Spatial Health And Population Estimator, Emma M. Von Hoene, Aanya Gupta, Hamdi Kavak, Amira Roess, Taylor Anderson

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling Social Isolation: A Data-Driven Index Function Design And Implementation, Jeremis N. Morales Morales, Carmen Caiseda, Phyllis Muniu, Joshua Atsu, Folashade B. Agusto

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Project Insight] Spatio-Temporal Analysis Of Domestic Violence In Puerto Rico, Phyllis Muniu

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

Global Cooling Watch 2025, Omar Abdelaziz, Ray Gluckman, Ian Hamilton, Radhika Khosla, Lily Riahi

Research Collection College of Integrative Studies

The second edition of UNEP’s Global Cooling Watch Report takes a deep dive into one of the decade’s most urgent challenges: surging heat, soaring cooling demand, and stark inequalities in access. Produced by the UNEP-led Cool Coalition, the report provides a comprehensive assessment of the rapidly growing global demand for cooling and the need for climate-friendly solutions to the issue. The 2025 report builds on the first Global Cooling Watch (2023), which established the Sustainable Cooling Pathway framework. The new edition deepens analysis of intensifying extreme heat and its effect on cooling demand, improved assessment of passive cooling, and coverage …

Rewilding The Built Environment: Navigating Economic, Political, And Social Barriers To Urban Ecological Restoration, Carly E. Smith

PANDION: The Osprey Journal of Research and Ideas

Urban rewilding offers a nature-based approach to restoring ecological processes in cities while advancing climate resilience, biodiversity, and public well-being. Unlike conventional green infrastructure, rewilding allows ecosystems to develop with minimal intervention, emphasizing succession, complexity, and long-term adaptability. This paper examines the political, economic, and social factors that frame how rewilding is understood and implemented in urban planning. Governmental frameworks often prioritize order, predictability, and short-term results, making it difficult to accommodate the uncertainty and ecological complexity that rewilding requires. Economic models struggle to capture its long-term value, frequently overlooking ecosystem services or reconciling competing land uses. Social perceptions of …