Projects

The focus of this project is on the analysis of UAS data rather than the data collection process itself. You are not required to collect your own UAS data; however, the dataset you use must be sourced from UAS data. Alternatively, your project could involve enhancing some aspect of UAS data collection, such as flight planning or Structure from Motion (SfM).

Available Data Sources:

  • Lake Wheeler (NCSU) - Agricultural Land: A dataset we will provide.
  • Utilize Open Data Sources
  • Collect Your Own Data: Optionally, you may choose to collect your own UAS data.

Proposal, presentation and paper requirements

Pre-Proposal

In the pre-proposal please define the scope of the project, the project location, data, and analysis you would like to perform.

Proposal

  • Define research question, select location, list available data, methods (theory), software tools, describe expected results.

Submit to Moodle

Presentation

  • Length: DE students 10 minutes, on-campus students 15 min + 5 min discussion
  • Introduction/background: problem, motivation for the research, research question / objective
  • Study site: where, why this site, geographic characteristics
  • Data acquisition: platform and sensor, flight plan (if applicable), flight conditions
  • Data properties and processing: resolution, spatial extent, accuracy
  • Analysis and/or modeling methods: describe methodology and workflows
  • Results: present and explain the results using qualitative and quantitative description, tables, graphs, maps/images
  • Discussion: discuss impact of flight conditions, data and methods on the results, uncertainty issues, compare with results from other studies, which questions remain unresolved, what still needs to be done
  • Conclusion: summary of the most important findings including advances in methodology, future work

Paper

  • Structure and formatting should follow scientific journal standards.
  • Same sections as the presentation
  • Text and Figures: min. 4 pages, single spaced including tables and references images, maps, graphs, presented in readable size with scale and legends where needed
  • References: at least 5 papers from scientific journals, rest can be reports, web documents
  • Appendix (optional): workflows, scripts, metadata. Software commands, issues go here

Past Projects

Projects 2021

  • Bartenfelder, Amy: Areal Changes at LAke Wheeler Field After the 2017 Hurricane Season
  • Webb, Andrew: Cabon Mapping of Agricultural Fields
  • Williams, Chantel: Northern Umstead State Park - Vegetation
  • Goodnight, Dallas: Can NC One Map Orthoimagery be used to accurately measure Cape Lookout Park shoreline elevation changes over time?
  • Wingler, Dylan: Using LiDAR to Compare Impact between Hurricane Matthew and Sandy on Cape Hatteras, NC
  • Pelfrey, Hank: Estimating Individual Tree Location and Height with UAS Photogrammetry
  • Dorner, Judy: Object detection in UAS Imagery Using Machine Learning Applications
  • Moy, Matthew: Creating and Interpolated DSM of Downtown Cary, NC
  • Perry, Marcus: Mars Science Helicopter: Exploring Photogrammetry with Ingenuity’s NavCam Data
  • Sawtelle, Macy: Testing the Capability of Unmanned Aircraft vehicles to Monitor Forest Regeneration Activities
  • Williams, Patrick: Using Unmanned Aerial System Imagery to Perform Solar Potential Analysis
  • Erlenbach, Peter: Image Classification Using Drone Data
  • Johnson, Randy: Urban Landcover Classification Utilizing UAS
  • Hill, Russell: Canyonlands National Park - 3D mash and a Scene Layer Package
  • Farrell, Sean: Multiple Return Lidar Analysis of Hydrologic Changes Due to Highway Flooding from Hurricane Florence
  • Tan, Samantha: The Impact of hurricane Events on Coastlines: Measuring Coastline Loss with Pre and Post Michael Orthophotogrammetry
  • Herzig, Bill: Drone vs Satellite - Multispectral NDVI Image Pixel Analysis

Projects 2020

  • Adams, Eric: Environmental Study Using UAS Data in the Edenton Bay, NC Region
  • Bert, Steve: Optimizing Parking Management for the City of Raleigh. An Unmanned Aircraft Systems Inventory Approach
  • Davis, Britt: Structure from Motion as a Participatory Design Tool: The Landscape Architect’s Guide to Better Models and Deeper Community Engagement
  • Franklin, Samuel: A Comparative Analysis of UAS in Archeology
  • McDonald, Christopher: UAS Technology for Mapping Urban Development – SouthEnd District of Charlotte, NC
  • Parish, William: UAS Implementation for Civil Engineering Design and Construction: NC 12 Bridge near Rodanthe Study
  • Phillips, Ryan: Evaluating the Effect of Image Resolution on Digital Surface Model Construction and Usefulness
  • Pierson, Gardner: The Use of High Resolution UAS Data vs Traditional Ariel Imaging to Predict Inundation and Potential Urban Impact on the Southern Slope of Mt. Etna, Italy, Using a Lava Flow Emplacement Model.
  • Signor, Kari: Exploring Lidar Classification Methods: Archaeological Applications in the Maya Lowlands
  • Spear, Michael: Using UAS Umagery for Land Cover Classification
  • Watts, Matthew: Exploring LiDAR in Area of Wildfire and Assessing the Benefits of Adding UAS Data

Projects 2019

  • Baker, Kurt: Effective ground classification of non-uniform laser data
  • Brown, Tamika: The Implications of Using Unmanned Aerial Systems to Monitor Hazardous Waste Facility Sites and Better Understand Community Endangerment within the City of Chicago
  • Charping, Charlie: UAS Technology for Open Pit Mining
  • Conrad, Matt: 3D Modelling from Video: Technology Application
  • Cummings, John: Automated Detection of Roadway Features Via UAS
  • Davis, Jeremy: Creating a Basis for the Influence of Elevation on Wheat Varieties in North Carolina
  • Groh, Erica: Proposed UAS Survey of Alluvial Fans in California
  • Hoffman, Dallas: Analysis of Multiple Return Lidar in ArcGIS
  • Jones, Alli: LIDAR and UAV to Monitor Beach Nourishment - Emerald Isle, NC
  • Ma, Xingli: Use of UAS to Detect Disease in Soybeans
  • Nicholas, D. Chase: Tracking Crop Development with UAVs: Using SfM to Estimate Plant Height and Volume
  • Oberrender, Daniel: Cave Detection using Local Relief Model derived from UAS SfM
  • Potter, Andrew: Coastal Change Analysis of the Cape Lookout National Seashore
  • Ruiz, Rachel: Implementation of Unmanned Aerial System to Conduct Bridge Inspection
  • Scheip, Corey: UAS Imagery to Supplement Lidar-Based Landslide Programs
  • Wheaton, James: Utilizing UAS to Generate Land Cover Data
  • Williams, Caleb: Unmanned Aerial Systems for Waterfowl Population Studies at the Tom Yawkey Wildlife Center

Projects 2018

  • Albert, James: A New Approach to Landfill Management in the Solid Waste Industry
  • Anderson, Alexander: Using UAS Structure from Motion and and LiDAR DSMs to Identify, Monitor and Mitigate Coastal Erosion In Okaloosa County
  • Bastias, Sabina and Montgomery, Kellyn: Combining Nadir and Oblique Imagery to Address Distortion in UAS Data
  • Catlow, Maureen, Hahn, Becca, and Voigt Erin: “RescUAV data after Hurricane Irma: Natural Disaster Analysis”
  • Dawson, Victor: ???
  • Edenhart-Pepe, Skyler and Pierce, Austin: Evaluating the use of time series UAS and Lidar data to monitor rate of change of hydrologic flow patterns on land development projects.
  • Felipe, Lauren: ???
  • Forte, Michael: Object Detection Using Structure From Motion Techniques
  • Howell, Andrew: Estimating Area and Standing Biomass of Zizania latifolia Using sUAS
  • Kesselring, Todd: Using LiDAR and NDVI for Vegetation Management in Utility Right of Ways
  • Lamb, Kelsey: Mapping surface water and impervious surface
  • Liesch, Mandy: Changes in Water Balance Associated with Farm Development
  • Meyers, William: Measuring and Modeling Biomass of Pines at Tatum Farm
  • Schrum, Paul: 3D UAV track in Blender: A Blender Addon to import, edit, then export UAV trajectories
  • Suffern, Carrie: Monitoring Drainage Issues at a Small Farm: Use of UAS DSMs and LiDAR DEMs to Forecast Storm Runoff and Monitor Sinkhole Formation
  • Vincent, Sarah: UAV versus Statewide Contours, is it worth it to move dirt?

Projects 2016

  • Travis Howell: Mapping volume of wood chip pile
  • Corbin Kling: Jockey’s Ridge State Park: a potential Mars dune analog
  • Nicholas Kruskamp: Forest structure
  • William Ross: Water Surface Elevation Generation & Storm Debris Volume Estimation using UAS
  • Joshua Rudd: Crop growth monitoring using sUAS

Projects 2015

  • Dyer Tristan: Barrier island monitoring of volume change
  • Foley Molly: Mapping forest fragmentation in urbanizing landscape using sUAS
  • Reckling William: Utilities
  • Bayasgalan Gantulga: Beaver dam impact assessment
  • Belica Laura: Monitoring grass conditions under different levels of management (change to solar irradiation from UAS DSM?)
  • Harmon Brendan: Gully monitoring and volume change assesment
  • Petras Vaclav: Optimizing point cloud density for modeling microtopography controls over surface flow.
  • Petrasova Anna: Extracting bare earth from sUAS using lower resolution bare earth lidar
  • Smart Lindsey Suzanne: Mapping coastal plain microtopography and its impact on surface water distribution
  • Velasquez Montoya Liliana: Mapping soil erosion using sUAS DEMs