Geographic Information Sciences Commons^™

Beyond "Place Matters": Making Spatial Analysis Accessible With Dashboard-Driven Geography, Stephen Borders

Public Health

This article presents an instructional module that uses Tableau to teach spatial thinking and policy geography through an analysis of Supplemental Nutrition Assistance Program (SNAP) participation. Tableau’s ability to integrate custom spatial files with demographic and health data makes it an accessible platform for introducing geographic inquiry without requiring specialized GIS expertise. The lesson guides instructors through building maps, bullet charts, and scatterplots that highlight gaps between eligibility and enrolment, while connecting food insecurity to health outcomes. By lowering technical barriers, Tableau provides a pedagogical bridge that helps educators foster spatial literacy in diverse classroom contexts.

This article was published …

Geospatial Analysis Of Urban Heat Islands And Heat Vulnerability In Chattogram, Bangladesh: Implications For Public Health Risks, Mst Sanjida Alam

Student Publications [Scholarly]

Rapid urbanization and land use change are intensifying the Urban Heat Island (UHI) effect and its associated health risks. It is the most common problem in the cities across the Global South. Chattogram the second-largest city in Bangladesh that has highly urbanized and experiencing transformation of croplands and vegetation into impervious surfaces. The changes contribute to the increase in the surface temperature and vulnerability of urban residents. This study aims to determine spatiotemporal patterns of UHI between 2011 and 2024 and the Heat Vulnerability Index (HVI) for 2024 and its associated health risk of Chattogram District. The HVI was developed …

Typeface: Machine-Viewing Gentrification On Storefront Imagery In Bedford-Stuyvesant, Brooklyn, Alexander Mcquilkin

Dissertations, Theses, and Capstone Projects

Gentrification—broadly, the replacement of a less powerful group by a more powerful one in an urban context—is oft-discussed in the popular press, but its definition is much-debated in the urban planning literature. Furthermore, academic treatments of displacement understandably focus on measurable yet fairly abstract indicators like changes in rent or income, whereas neighborhood change is often registered by residents on the ground using visual, but difficult-to-quantify markers like retail turnover. This project uses image recognition technology on a set of storefront photos to index the visual streetscape of a neighborhood, as well as to track changes to that portrait over …

A Student-Centered Gis Classroom: Second Chances And Real-World Practice Teaching Portfolio For Nres218 Introduction To Geospatial Technologies, Ran Wang

UNL Faculty Course Portfolios

This course portfolio documents the design, implementation, and reflection of NRES218 Introduction to Geospatial Technologies, an introductory undergraduate geographic information system (GIS) course. This course aims to integrate basic and applied sciences to help students develop spatial thinking and spatial analysis skills for proposing spatial science–oriented solutions. Instructional strategies emphasize experiential learning through structured laboratory exercises and outdoor field activities that connects real-world observation with GIS analysis. To support student learning and persistence, the course also incorporated flexible assessment practices, including second-chance exams. Reflection on student engagement and performance revealed that while these strategies were highly beneficial for some students, …

Spatiotemporal Assessment Of Coastal Urban Heat In Buenos Aires Using Satellite Landsat Lst, Noah Morales, Lleyton Naar, Dan Macchiarella, Kevin Adkins, Ronny Schroeder

Student Works

Coastal urban environments exhibit complex surface temperature patterns driven by interactions among water, vegetation, and built infrastructure. This study investigates land surface temperature (LST) variability along a coastal-to-urban transect in Parque de los Niños, Buenos Aires, by integrating multi-year satellite Landsat LST with high-resolution thermal data collected from an uncrewed aircraft system (UAS). Landsat provides the temporal depth necessary to assess seasonal and interannual variability in surface temperature, including responses to extreme summer conditions. However, their spatial resolution limits the ability to resolve fine-scale thermal gradients near shoreline boundaries and within heterogeneous urban landscapes. UAS thermal observations address this limitation …

Geospatial Investigations Of Big Buckhead Cemetery, Millen, Ga, Audrey E. Popard

College of Graduate Studies: Theses & Dissertations

Geospatial investigations of burials are increasingly recognized as the most efficient and ethical means of determining grave locations in forensic and bioarchaeological research. A methodology of multi-tiered geospatial investigation has been applied to the Big Buckhead Baptist Church cemetery in Millen, GA. Using the systematic layering of geospatial technologies, the present study seeks to identify ground surface anomalies, with the objective of delineating known and potential unknown burial locations. It is hypothesized that the layered use of Light Detection and Ranging (LiDAR), Geographic Information Systems (GIS), and Ground Penetrating Radar (GPR), will allow for the most efficient and accurate demarcation …

Integrated Geospatial Analysis Of Burn Severity And Vegetation Recovery Of The California August Complex Fire In 2020, Dharm Barot, Ronny Schroeder, Elise Anderson

Student Works

Large wildfires increasingly alter vegetation structure and ecosystem recovery trajectories at landscape scales, requiring reliable geospatial methods for post-fire assessment. This study evaluates burn severity and vegetation recovery following the 2020 California August Complex Fire using an integrated framework combining multispectral satellite imagery, spatial statistics, and airborne LiDAR data.

Burn severity was quantified using differenced Normalized Burn Ratio (dNBR), and vegetation recovery was assessed through a multi-temporal NBR time series spanning pre-fire (2015), fire-year (2020), and post-fire (2025) conditions. Optimized Hotspot Analysis (Gi*) was applied to isolate statistically significant clusters of high burn severity and reduce bias in recovery estimates. …

Validating Uas-Based Ndvi Data With Satellite Landsat Imagery For Bald Eagle Habitat Prediction In The Del Rio Springs Ecosystem, Noah Morales, Colton Weeks, Hank Vincent, Ronny Schroeder

Student Works

Vegetation health is commonly assessed using the Normalized Difference Vegetation Index (NDVI), which can be derived from multispectral sensors operating at different spatial resolutions. Validating NDVI products across sensor platforms is essential to determine their reliability for environmental monitoring and habitat assessment. This research compares NDVI derived from moderate-resolution satellite imagery and high-resolution unmanned aircraft system (UAS) imagery collected over the same study area. Landsat imagery, provided through the joint USGS–NASA mission, was used to represent satellite-based vegetation patterns, while high-resolution multispectral data were acquired using a MicaSense sensor mounted on a UAS to capture fine-scale vegetation detail.

NDVI values …

Integrated Geospatial Analysis Of Burn Severity And Vegetation Recovery Of The California August Complex Fire In 2020, Dharm Barot, Ronny Schroeder

Student Works

Large wildfires increasingly alter vegetation structure and ecosystem recovery trajectories at landscape scales, requiring reliable geospatial methods for post-fire assessment. This study evaluates burn severity and vegetation recovery following the 2020 California August Complex Fire using an integrated framework combining multispectral satellite imagery, spatial statistics, and airborne LiDAR data.

Burn severity was quantified using differenced Normalized Burn Ratio (dNBR), and vegetation recovery was assessed through a multi-temporal NBR time series spanning pre-fire (2015), fire-year (2020), and post-fire (2025) conditions. Optimized Hotspot Analysis (Gi*) was applied to isolate statistically significant clusters of high burn severity and reduce bias in recovery estimates. …

Precision Rockslide Hazard Mapping With Multispectral Imaging And Lidar Along Arizona Highway 89a, Hank Warner, Ronny Schroeder

Student Works

Along mountainous roads, rockslides, mud slides and avalanches pose a significant risk for continued access to a region and can cause large amounts of damage to infrastructure, taking time to clear and repair. The prediction of where these events will occur can allow preventative measures to be taken, allowing sustained access and preventing costly repairs.

This study develops a method to analyze and predict rockslide risk using satellite-sourced multispectral imagery and airborne LiDAR data.

The developed method started with multispectral LANDSAT 8 imagery and airborne LiDAR captures over Arizona Highway 89A, with all data taken between late August and early …

Assessment Of Truck Parking Demand And Safety During Normal And Severe Weather Conditions In Nebraska, Nathan Huynh, Li Zhao, Zhenghong Tang, Aida Riahifar, Jahangeer Jahangeer

Nebraska Department of Transportation: Research Reports

This project examined truck parking capacity, demand, and utilization patterns along I-80 in Nebraska. The objectives were to (1) document the capacity of public and private truck parking facilities along I-80, (2) analyze spatial and temporal trends in parking demand, (3) develop models to predict occupancy at parking facilities, (4) identify clusters of undesignated parking during inclement weather, and (5) assess whether truck parking shortages contribute to truck-involved crashes. Within a one-mile buffer of I-80, 21 public facilities and 49 private facilities were identified. The spatiotemporal analysis of these public and private truck parking facilities using the National Agriculture Imagery …

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 …

Model Data Of "Aerial Imagery Resolution Optimization And Machine Learning Model Comparison For Land Cover Classification", Jessica Suoja

Research Data Sets

Downloadable zip file contents:

• 1MeterModel.csv (CSV file, 8.5 KB)
• 1MeterPrediction.csv (CSV file, 81.4 MB)
• 2MeterModel.csv (CSV file, 9.6 KB)
• 2MeterPrediction.csv (CSV file, 20.8 MB)
• 5MeterModel.csv (CSV file, 9.1 KB)
• 5MeterPrediction.csv (CSV file, 2.4 MB)
• 50CentimeterModel.csv (CSV file, 9.7 KB)
• 50CentimeterPrediction.csv (CSV file, 333.3 MB)
• 75CentimeterModel.csv (CSV file, 9.6 KB)
• 75CentimeterPrediction.csv (CSV file, 147.0 MB)
• 1125MeterModel.csv (CSV file, 9.0 KB)
• 1125MeterPrediction.csv (CSV file, 65.8 MB)
• 125MeterModel.csv (CSV file, 9.6 KB)
• 125MeterPrediction.csv (CSV file, 53.1 MB)
• 1375MeterModel.csv (CSV file, 9.5 KB)
• 1375MeterPrediction.csv (CSV file, 44.1 MB)
• 150MeterModel.csv (CSV file, 9.0 KB)
• 150MeterPrediction.csv (CSV file, 37.0 MB)
• 175MeterModel.csv (CSV file, 9.6 KB)
• 175MeterPrediction.csv …

Model Data Of "Land Cover Classification Of A Desert Riparian Ecosystem Using A Basic Stacked Ensemble Modeling Approach", Jessica Suoja

Research Data Sets

Downloadable zip file contents:

• CARTscript.R (R script, 2.2 KB)
• ForModel.csv (CSV file, 9.5 KB) 
• ForPrediction.csv (CSV file, 44.1 MB)

Identifying Socio-Economic Areas Of Concern Towards Inclusion In Gis Hazard Management In Detroit, Michigan., Ernestina Osei

Master's Theses or Doctor of Nursing Practice

This study examined the spatial distribution of socio-economic vulnerability and accessibility to essential services in Detroit, Michigan, using a Geographic Information Systems (GIS)-based approach. The research aimed to identify areas of greatest concern by integrating socio-economic indicators, including poverty, housing vacancy, income, unemployment, and crime, with spatial measures of access to critical infrastructure such as hospitals, fire stations, police stations, and grocery stores. Both feature-based and raster-based analyses were employed, including buffer and overlay analysis, service area evaluation, Euclidean distance modeling, and multi-criteria suitability analysis.

A mixed-methods framework was adopted to combine quantitative spatial analysis with contextual understanding of urban …

Improving Flood Risk Mapping By Incorporating Local-Scale Calibration Data Derived From Stakeholder Input, Jennifer M. Holifield, Wei Wu, Patrick D. Biber, Margo Posten, Dennis Mcgrury, Stephen C. Deal, Alexandria Hancock

Gulf and Caribbean Research

Globally, flooding is the most frequent and costly natural hazards, disproportionately affecting populations based on environmental, social, and economic factors. Understanding the spatial variability of flood risk as well as the respective flood drivers is essential for informing cost-effective mitigation strategies and enhancing community resilience. Here we mapped flood risk that combines flood hazards and vulnerability in an under-resourced coastal community prone to compound flooding. Our approach integrates stakeholder engagement with GIS-based analysis using open-access datasets.

We first developed an initial flood hazard map using an equal-weight combination of factors commonly associated with flood occurrence/prevention, including upslope area, impervious surface …

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 …

Enhancing Coastal Vulnerability Assessments And Policy Impacts On Socioeconomic And Environmental Equity In Michigan's Great Lakes Communities, Esther N. Acheampong

Dissertations, Master's Theses and Master's Reports

Accelerating shoreline erosion, fluctuating lake levels, and climate-induced hazards are transforming the Great Lakes’ freshwater coasts, exposing the limitations of static and inequitable management frameworks. This dissertation investigates how Michigan’s coastal governance systems produce and manage vulnerability along the Lake Michigan shoreline by integrating geospatial modeling, institutional policy analysis, and environmental justice theory. It argues that both physical processes and institutional designs co-determine patterns of exposure, protection, and equity. The research begins by developing a refined Coastal Vulnerability Index (CVI) tailored for lacustrine environments, applying it to Muskegon County to assess how shoreline change, armoring, and seasonality influence localized risk. …

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 …

Modeling Inundation Susceptibility, Dengue Fever Risk, And Social, Ecological, And Technological Vulnerability To Climate Change At Small Geographic Scale In Thailand, Zachary Alan Zoet

Graduate Research Theses & Dissertations

The climate is changing, and the livelihoods of more than 3.3 billion people are presumed to be vulnerable to a climate altered significantly from historical norms. Despite international concerns that ramifications of climate change may affect environmental conditions in ways that could exacerbate inundation, dengue fever incidence, and social vulnerability in large areas of the planet, research focused on revealing the roots of these problems tends to cover small areas at large geographic scales. Inconsistencies in research design elements that may ramify from data classification regimen and misappropriation of variable selection, non-consensus about unit of analysis or scale, and disagreement …