Remote Sensing Commons^™

Cropland Change And Prime Farmland In Calloway County, Kentucky, 2015–2025: A Gis Analysis Of Corn And Soybean Fields, Shiba Hari Dhakal Shiba

Scholars Week

Understanding where cropland change occurs relative to soil quality helps indicate whether farmland is being used on the most productive land. This study used GIS-based change detection analysis to evaluate changes in corn and soybean fields in Calloway County, Kentucky, between 2015 and 2025 and to test whether new corn and soybean fields were located on prime farmland. USDA Cropland Data Layer maps for 2015 and 2025 (30 m resolution) were reclassified into seven classes and compared in ArcGIS Pro, and the results were overlaid on USDA NRCS gSSURGO farmland classification. Combined corn and soybean area declined about 19% from …

From Disaster To Resilience: Developing Smart Settlements In The Himalayas, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

Nepal’s catastrophic 26 August 2026 Bhote Koshi–Trishuli flood should be understood not only as a humanitarian tragedy but also as a potentially major turning point in updating national settlement and reconstruction policy. Engineers and scientists have described the floods as a glacier–bedrock collapse that triggered an ice-rock avalanche and debris flow. As per the live updates on September 7, 2026, the total death toll was 1,355, and 4,996 people were missing (The Hindu, 2026). Indian and Nepali rescuers worked urgently to locate and rescue people buried under hydropower tunnels, buildings, mud, and landslide debris.

UN News reported on September 3, …

From Himalayan Catastrophe To National Resilience: Lessons From The 2026 Bhote Koshi And Trishuli River Floods In Nepal, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

On the morning of 26 August 2026, the mountains above Nepal’s northern frontier delivered a disaster of almost unimaginable speed and scale. A massive mass of ice, rock, and sediment detached in the high Himalayan terrain near the Nepal–Tibet border, descended roughly 1,200 metres, interacted with the Lhende Khola system, and generated a debris-rich flood that surged through the Bhote Koshi and Trishuli river corridors, destroying settlements, markets, roads, bridges, hydropower facilities, and an international border crossing and transforming them into fields of mud, boulders, and wreckage within minutes (ICIMOD, 2026b; Reuters, 2026a). Satellite analysis indicates that a substantial section …

Modeling Bald Eagle Habitat Suitability In The Del Rio Springs Ecosystem Using Lidar And Spatial Analysis, Noah Morales, Hank Vincent, Ronny Schroeder

Student Works

This study expands upon prior research that utilized NDVI-based hotspot analysis from UAS and satellite imagery (Morales et al. 2026) to identify potential bald eagle nesting and foraging areas. While NDVI effectively captures vegetation density, it does not distinguish between vegetation types or landscape structural characteristics necessary for nesting. To address this limitation, this research integrates LiDAR-derived canopy height, terrain slope, and proximity to stream networks to develop a more refined habitat suitability model within the Del Rio Springs ecosystem.

Airborne LiDAR data were used to generate Digital Surface Models (DSM) and Digital Elevation Models (DEM), which were employed to …

Morphometric Analysis Of Gypsum Depressions Using Drone Imagery At Sinkhole Flat, Eddy County, New Mexico, Usa, Michael Sean Chenoweth

Research, Publications & Creative Work

Morphometric analysis is conducted on five karst depressions in Permian-age gypsum of southeast New Mexico. These depressions take on the form of classically shaped blind valleys and sinkholes. Blind valleys in this study are disappearing surface streams composed of multiple tributaries that connect to the main trunk channel leading to a cave entrance. A visible light (RGB) sensor mounted on a quadcopter is used to collect aerial imagery for karst depression mapping and analysis. Field measurements were taken for each depression for comparison with the drone imagery and its derivative layers such as digital elevation model (DEM) and slope. Drone …

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 …

Scraping The Earth: Testing Ndvi As An Indicator Of Military Ground Maneuver Within The Israeli Invasion Of The Gaza Strip, Thomas A. Bergeron

LSU Master's Theses

The advancement of open-source (OSINT) and geospatial intelligence (GEOINT) has allowed independent researchers to study human conflict in new ways, with tools that were previously reserved only for state intelligence agencies. In order to advance methodologies, researchers must continue to evaluate new tools to study war.  Valued for its accessibility and moderate spatial resolution, the Normalized Difference Vegetation Index (NDVI) is one such tool that has not been widely systematically tested for its use in an open-source GEOINT investigation of modern conflict. This study tests NDVI as an indicator of military maneuver by leveraging a mixed-method approach against open-source kinetic …

Gis-Based Solar Energy Suitability Assessment For Utility-Scale Photovoltaic Development In Texas, Deepak Kumar

Masters Theses

This research developed a GIS-based multi-criteria suitability model to identify sites in Texas favorable for utility-scale solar photovoltaic (PV) development. The model integrated three biophysical variables—Global Horizontal Irradiance (GHI), terrain slope, and land cover—within a weighted overlay framework using the Analytic Hierarchy Process (AHP) for criteria weighting. GHI data were derived from the ERA5-Land Daily Aggregated dataset (ECMWF, 2024), slope was calculated from the USGS 3DEP 10-meter Digital Elevation Model, and land cover was classified from the National Land Cover Database 2021 (USGS). Each variable was reclassified to a 0–4 suitability scale and combined using AHP-derived weights of 0.50 (GHI), …

Increasing Accuracy Of Mapping Local Climatic Zones Using Building Height And Spectral Unmixing, Ian Douglas Stauffer

Masters Theses

Local climatic zone (LCZ) classifications are traditionally done using reflectance, population data, and often climatic data. The goal of this research is to utilize Google’s new “Open Buildings Temporal v1” building data set as well as “spectral unmixing”. With the objective of testing, assessing, and implementing this data set into the workflow of LCZ mapping. After testing the quality of the data against a validated LiDAR data set from the same year as a given “Open Buildings Temporal v1” band, I implemented it into the Random Forest machine learning process. Secondly, I justified the use of spectral unmixing as a …

Machine-Learning Landslide Susceptibility And Runout Modeling In The Nolichucky River Gorge After Hurricane Helene, Grace Braver

Electronic Theses and Dissertations

Extreme rainfall from Hurricane Helene (September 2024) triggered widespread landslides across the southern Appalachian region, highlighting the need for rapid landslide susceptibility assessments that capture both landslide initiation and downstream runout. Traditional susceptibility models often focus solely on initiation zones, limiting their ability to identify which slopes will generate destructive landslides or where material will travel. This study addresses that gap by (1) integrating Geographic Information System (GIS)-based machine learning susceptibility modeling using ArcGIS Pro: Maximum Entropy (MaxEnt) and Random Forest-Based and Boosted Classification and Regression (FBBC) and (2) the U.S. Geological Survey (USGS) Grfin (Growth, Flow, and Inundation) runout …

Applications Of Suas Thermal Imaging And Lidar At Letort Spring Garden Preserve: An Independent Study, Kelsey Wardell

Harrisburg University Other Works

No abstract provided.

Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert

International Journal of Speleology

This study investigates the relationship between sinkhole occurrence and distance to drainage in the Sivrihisar region (Central Turkey) and evaluates the suitability of different regression approaches for modeling clustered count data in karst terrains. A comprehensive inventory of 104 sinkholes developed within the Neogene lacustrine limestones of the Akpınar Formation was compiled using official records, remote sensing analyses, and detailed field surveys. Sinkhole occurrences were analyzed relative to a drainage network derived from a high-resolution Digital Surface Model and grouped by proximity to drainage lines. Linear Regression (LM), Poisson Regression (PR), and Negative Binomial Regression (NBR) models were comparatively applied …

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

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 …

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, …

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 …

Validating Uas Lidar With Airborne Lidar For Precision Streamline Generation In Del Rio Springs, Arizona, Brad Rudy, Colton Weeks, Hank Vincent, Ronny Schroeder

Student Works

Accurate streamline delineation and high-resolution topographic products are essential across numerous disciplines, including hydrological analysis, environmental monitoring, construction, and erosion modeling. Products derived from high-accuracy elevation data provide greater reliability and improved decision-making outcomes for all fields that depend on them. A 2018 USGS airborne LiDAR dataset covering the Del Rio Springs riparian area north of Chino Valley, Arizona, offers a valuable opportunity to evaluate the relative accuracy of the DJI L1 LiDAR sensor when mounted on a Matrice 300 RTK UAV platform. Compared to traditional manned airborne systems, the UAV-mounted L1 provides high-accuracy, high-density point cloud data over small …

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. …

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. …

Geospatial Analysis Of Wildfire Ignitions And Proximity To Electric Transmission Lines In Arizona’S National Forests, Shane Ishmael, Ronny Schroeder

Student Works

The number of wildfires in Arizona rose by 18% from 2023 to 2024. Wildfires hit the Western United States hard, especially in states like Arizona and California, where vast national forests often fall victim to the biggest blazes. According to the Western Fire Chiefs Association, 19% of wildfires from 2016 to 2020 were sparked by electrical transmission lines.

This study explores whether wildfire start-location hotspots line up with power transmission routes running through Arizona’s Coconino and Tonto National Forests. The main hypothesis is that areas near power lines are more likely to become wildfire hotspots than other regions.

We used …

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 …

Climate Change In Gilgit-Baltistan: Satellite-Based Land Use/Land Cover Change Detection, Socio-Economic Dimensions, And Adaptation Strategies, Ali Muhammad

Graduate Theses/Dissertations

Climate change is increasingly transforming the cryosphere, hydrology, and human landscape of Gilgit-Baltistan, a highly climate-sensitive mountain region in northern Pakistan. This thesis investigates these transformations through satellite-based land use/land cover (LULC) change detection in four representative tehsils of Gilgit-Baltistan—Ali Abad, Gilgit, Nagar, and Sikander Abad—selected to span a gradient of human pressure and cryospheric exposure within the region. Using summer, cloud-free (< 10%) imagery from USGS Landsat 7 (2000) and Landsat 8 (2025), it conducts a multi-temporal comparison of environmental and socio-spatial change. After atmospheric correction and band compositing, the imagery is classified in ArcGIS Pro into six classes—Water, Barren land, Vegetation, Snow, Glacier, and Built-up—using a Support Vector Machine (SVM) classifier, with Maximum Likelihood Classification and Random Forest also tested but found less suitable for the final workflow. The analysis detects a pronounced reduction in mapped glacier-class area alongside a comparatively stable snow class, together with built-up expansion, while examining how temperature, precipitation, tourism, and population dynamics relate to observed LULC transitions. The results reveal a pattern of cryospheric decline and urban growth, with implications for water availability, ecological stability, hazard exposure, and settlement pressure. By integrating geospatial change detection with climatic and socio-economic interpretation, the thesis moves beyond mapping to explain interacting environmental and human drivers of landscape transformation and provides a reproducible remote-sensing baseline for monitoring land-surface change in heterogeneous mountainous terrain. It recommends integrated water-resource management, climate-resilient land-use planning, watershed and glacier monitoring, and sustainable tourism governance, supporting evidence-based decision-making by the Government of Gilgit-Baltistan and organizations working on climate adaptation, disaster risk reduction, and sustainable regional development.

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 …

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 …

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 …

Analyzing Sea Level Rise Scenarios Impact On The Mobility, Infrastructures, Environment Of Abu Dhabi And Defining Solutions By Creating A Digital Twin Using Gis And Game Engine, Justine Sylviane Lucie Sarrau

Thesis/ Dissertation Defenses

This dissertation is concerned with the potential impact of future sea level rise scenarios on the city of Abu Dhabi. With climate change, many coastal towns are at risk of experiencing this type of natural hazard. Currently, no precise scenario simulations have been developed, mainly related to the use of low spatial resolution elevation data. Additionally, the difficulty in understanding the real impacts persists when relying solely on traditional cartography and GIS methods. This dissertation mainly aims to take a further step by offering a new approach, which involves creating a real-time 3D simulation and dynamic flowing water. This is …

Near Real-Time Monitoring Reveals Extensive Recent Forest Disturbance In Ghana’S Protected Areas, Luofan Dong, Xiaojing Tang, Foster Mensah, Bashara Ahmed Abubakari, Kelsee H. Bratley, Pontus Olofsson, Curtis E. Woodcock

Faculty Scholarship

The Protected Areas (PAs) in Ghana play a critical role in preserving the abundant biodiversity of the West Africa Green Belt. But recent changes in policies and regulations have facilitated logging and mining activities, which have accelerated forest disturbances. While there is a consensus that PAs are undergoing destructive change, the extent, rate, and locations of forest disturbances are undocumented. In this study, we applied the fusion near real-time (FNRT) algorithm that utilizes Landsat, Sentinel-1, and Sentinel-2 data and sampling to monitor forests in the PAs of Ghana. The results reveal that 704.74 (±177.24) km2 of forest in the PAs …

Remotely-Sensed Urbanization And Local Perceptions Of Change From 1985-2024 In Southern Indiana., Marlea Ferber

Electronic Theses and Dissertations

This study is focused on the land cover change of non-built land cover being transformed into built land cover in two counties in Southern Indiana using mixed methods. Remote sensing was used to identify and quantify land cover change, and interviews were used to understand local perceptions of the physical land cover changes. The study area is situated along the rural-urban continuum with Louisville, Kentucky across the Ohio River. It is important to quantify the amount of land change conversion to built settlement as patterns and rate of urbanization help us to better manage transitions along the rural-urban continuum, but …

The Dynamics Of Urbanization And Changes In Ekistics Elements: A Case Study Of Surakarta City, Sarah Astita

Cities and Urban Development Journal

Urbanization has become a driving force behind significant spatial, environmental, and socio-economic transformations in urban areas, including Surakarta, the most densely populated city in Central Java. The rapid increase in population and urban expansion has led to drastic changes in land use and the structure of human settlements. This study aims to analyze the impact of urbanization on the ekistic elements of Surakarta (nature, humans, society, space/shells, and networks) and how these changes manifest spatially over time. A descriptive qualitative approach is employed using literature analysis and the interpretation of Landsat satellite imagery from 2011 and 2022. The findings show …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Kabe Aberle, Nadia Kako, Kateri Mcrae, Brooke Agulnek, Sky Palmon, Yasmine Ramirez, Francisca Aguirre Beltran, Ashley Juarez, Bridget Kim, Tessa Appel, Sterling Kerr, Spencer Ingley, Gabe Meyer, Robin Tinghitella, Dale Broder, Lily Baeza, Chloe Beers, Julia Coakley, Whitney Kelsey, Sydney Gainforth, Gabi Wing, Audrey Martin, Aaliyah Amore Berry, Brooke Watley, Kiruthika Venkatesan, Rachel Bienstock, Annabella Brotherston, Madison Bryant, Mia Burgener, Emma P. Lieb, Rachel A. Johnson, Jennifer L. Hoffman, Kania Campbell, Kiena Campbell, Courtney Cassidy, Sage Krzyzkowski, Maddox Jones, Skylar Abookire, Luke Hawkins, Sunnah Yoon, Andrea Chu, Yan Qin, Nyah Cubbison, Brian Gearity, Daniel Mcintosh, Mariely Cruz, Edward Garrido, Grady Dionne, Nicole Doris, Lyndsie Salvagio, Ann-Charlotte Granholm-Bentley, Anna Dymov, Hannah Eckert, Gabrielle Welsh, Erica Larson, Charlie Ernst, Anna Zhou, Sarah Watamura, Larissa Fedorovich-Klein, Georgie Fields, Kimberly A. Guevara, Aven Mccall, Ben Peltier, Feruz Yahia, Patrick Flores, Jadyn Floyd, Sophia Forcier, J. Von R. Monteza, Peter Sokol-Hessner, Gwendolyn Geiger, Scott Nichols, Camryn Gunter, Kendal Hengst, Charlie Bednarz, Issy Garside, Addison Baker, Rachel Mina, Brooke Hermanson, Amanda Klingler, William Highfill, Sydney Jaques, Kerstin Lewey, Allison Grossery, Daniel Linseman, Ethan Lim, Jagger Livengood, Owen Mantelli, Gabby Pappas, Abby Mcdonald, Madeleine Dierking, Eve Miller, Emma Loeber, Anna Marlow, Michael Kerwin, Ella Mathews, Hillary Hamann, Khadija Mohamed, Vivian Nguyen, Gabri Notov, Ifunayachi Ogbonna-Ukuku, Sunil Kumar, Charles Baysah, Sarah Olson, Don Sullivan, Anna Paradiso, Jay Parrish, Mira Pronobis, Alisha Pravasi, Kerstin Haring, Diego Ramirez, Christopher Reardon, Juliana Ramirez, Casey Doherty, Ella Kestner, Teagan Weindel, Cate Billings, Pablo Torre-Walter, Lucy Rand, Samantha Reynolds, Mark Siemens, Khadeeja Rashid, Laine Satterlee, Piper Heilbronner, Lily Pound, Ben Whitehurst, Anna Respet, Lizzie Lesoing, Sydney Hertel, Aya Saad-Masri, Brooke Ballenger, Max Proske, Hannah Rosenberg, Ellia Nakahara, Sophia Espinoza, Ivan Woolhouse, Simon Ruland, Gorkem Er, Timothy Sweeny, Melaku Saketa, Michela Schenk, Maren Lynch, Madi Hamm, Grace Schroeder, Michelle Rozenman, Rana Seif, Jackson Hall, Marisela Simental, Daniel Paredes, Aaron Mena, Preston Spaan, Evelyn Stovin, David Andrew Swartz, Anh Tran, Daniel Pittman, Luke Farchione, Emily Boyer, Ukari Verner, Lacey Conrad, Jonathan Velotta, James Weiner, Jagger Gossett, Noah Sherry, Sam Proud, Ben Block, Avi Narayana, Zoey Weiss, Alyssa Wilson, Gabrielle Walsh, David Zonana, Keely Wright, Kena Riveria, Lillybelle Deer, Jena Doom, Elysia Davis, Isabelle Yaremenko, Caitlyn Young

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

Flood Risk Assessment In Humanitarian Contexts: A Remote Sensing And Gis Methodology Applied To Nyarugusu Refugee Camp, Tanzania, Carolyne Vincent Mbirika

Theses

Flooding is a global challenge, with effects mostly experienced in developing countries due to insufficient data for effective flood risk assessment and management. Refugee settlements are particularly vulnerable to flooding due to their remote locations, high population density, and temporary shelters, necessitating flood susceptibility mapping to effectively mitigate risks and minimize damage prior to flooding events. This study assessed flood susceptibility in the Nyarugusu refugee camp, Tanzania, through Multi-criteria Decision Analysis (MCDA) and Analytical Hierarchy Process using remote sensing and Geographic Information Systems (GIS) approaches. The flood susceptibility map that resulted from this process categorizes flood-prone areas into three classes: …