NCSU GIS 714:
Geospatial Computing and Simulations

Projects

The following project assignments will be required:

  • proposal (min 2 pages) and proposal lightning talk (3 min)
  • project progress short talk (8-10 min + discussion)
  • project presentation (15 min + discussion, optionally in Hunt library)
  • paper (min 6 pages, github repository and/or Jupyter notebook optional)

Proposal requirements

Preferably, work on your dissertation research focusing on its geocomputing or simulations component. You can get inspired by the material covered in this course (see the course Topics) or the past projects with the titles listed further below. You can use any suitable software tools or computing environments.

Project proposal should include the following sections: Title, Introduction, Objective or research questions, Study site, Data, Proposed methods and tools (any software or combination can be used), Expected results, References. The proposal should be at least 2 pages long including references (feel free to write more if you are building upon previous proposal) and include at least one image of your study site or data. Information about targetted scientific journal should be included.

Project progress report

Project progress report should be written as initial draft of your paper and it should include the following sections: Title, Introduction (less than 1 page), Objective or research questions, Study site, Data, Methods, Preliminary and Expected results, References. The progress report should be at least 3 pages long including references and include at least one image of your study site or data and an image of preliminary results or analysis. Information about targetted scientific journal should be included.

Project progress and final presentations

Project progress presentation is 8-10 minutes, the final presentation is 15 minutes. The structure follows organization of the paper (see below). For the project progress presentation discuss what still needs to be done and what may be holding you back. Also discuss how this project and paper fits with your dissertation.

Paper requirements

Structure and formatting should follow scientific journal standards, preferably for your targetted journal. Please read and follow 11 steps to structuring a science paper

  • Text: minimum 4 pages, single spaced including tables and references
  • Figures: mininmum 2 pages, images, maps, graphs, all should have readable size, scale and legends where needed

Organization of the paper

  • Introduction/Background: brief literature review, motivation for the research, research question / objective
  • Study site: where, why, geographic characteristics
  • Data: sources, don't forget to discuss selection of resolutions, spatial extent
  • Methods: describe methodology, highlight any new approach that you have developed
  • Results and discussion: present and explain the qualitative and quantitative results, including tables, graphs, maps/images; compare with results from other studies (confirmed previously observed phenomena, showed something new, which questions remain unresolved
  • Conclusion: summary of the most important findings including advances in methodology, future work
  • References
  • Appendix: link to github, workflows, commands, scripts, metadata, software-specific issues
  • Optional: Jupyter notebook, data repository, online tool
Further notes:
  • Use scientific language, this is a technical paper for experts in your field
  • Spelling errors are unacceptable
  • Images: use your own images/figures, make sure the figures are readable, use well designed color ramps, add scale bar and legends

Spring 2023 projects

April 19

  • Emma Butzler: Predicting the probability of septic system installations for future development
  • Jenna Abrahamson: Integrating Physical and Remote Sensing Models to Map Inundation at High Spatiotemporal Resolution
  • Randi Butler: Drought impacts on crops
  • Truffaut Harper: A Computational Framework for FUTURES Grows Up
  • Eli Horner: Quantifying and partitioning uncertainty in forecasts of Sudden Oak Death
  • Owen Smith: Rethinking Computationally Intensive Remote Sensing Sciences: A Statistical Approach to Mixed-Resolution Data Synthesis (Focus on spatial scale)

April 26

  • Grace Choi: Is the end of growing season earlier in drylands compared to non-drylands during times of drought?
  • Rebecca Composto: Quantifying Urban Flooding Extent Using Satellite Imagery and Population Impacted After Hurricane Ida in Philadelphia, PA
  • Mark Feinberg: Accounting for Uncertainty in Crop Loss Estimate in North Carolina
  • Jamie Huerta: Analyzing spatiotemporal trends in DON from 2018- present in the Chowan River & Albemarle Sound
  • Christina Perella: Modeling climate-driven migration in the Southern Appalachia region of North Carolina
  • Deja Perkins: An Equitable Christmas Bird Count? Sampling Site Suitability Across North Carolina

Spring 2022 projects

  • Dunstan,Christopher: Dance analysis using computer vision
  • Goodall Louis: Assessing the effects of disturbance upon forest productivity and forest biodiversity/carbon sequestration
  • Lawrimore,Margaret Aileen: Influence of Zoning on Urban Development
  • Paulukonis,Elizabeth: Quantifying spatiotemporal trends in pesticide toxic loading using a novel field delineation approach: a case study using Bombus. affinis
  • Reckling,Stacie K: Geospatial methods to support COVID-19 wastewater surveillance
  • Shannon,Andrew: Developing a neighborhood light model to evaluate oak regeneration efforts in Southern Appalachia
  • Tiwari,Varun: Rice area mapping in Bangladesh; Harnessing the power of time-series SAR data, Machine Learning algorithm, and Google Earth Engine

Spring 2021 projects

Tuesday April 20, 2021

  • Muyiwa Adeyeye: Flood Analysis for Socio-Economically Challenged Hazard Regions Along the U.S. Virgin Islands
  • Luke Allen: Relating Waves in Pressure Sensor Data to Waves in Radar Velocity Data
  • Das Raja: Machine Learning-based mapping of landslide initiation zones and flow channels using satellite imagery
  • Nicholas Grokhowsky: Using spread simulation to predict research bias in public health research throughout the United States
  • Caitlin Haedrich: Updating and Generalizing Blender Rendering for Tangible Landscape

Tuesday April 27, 2021

  • Izzi Hinks: Optimizing The Utility Of Minimal VHR Data In Studies Of Smallholder Farms
  • Brit Laginhas: Accurate Spotted Lanternfly forecasting is contingent on methods used to estimate Tree- of-Heaven host maps
  • Martine Mathieu: Spatial Interpolation of Fine Particulate Matter Concentrations Produced During Wildfires
  • Uchenna Osia: Manifestations of Environmental Racism in Historically Redlined and Gentrified Neighborhoods
  • John Polo: Using simulation to design sensor sample protocol and model infestation of multiple crop hosts by late blight
  • Ariel Saffer: Sensitivity analysis of initial conditions for global invasive pest forecasting (Pandemic model)

Spring 2020 projects progress short talks

Tuesday February 25

  • Xiaojie Gao Modeling forest productivity by management strategies and phenology
  • Kate Jones Simulating future fires within varying socio-ecological scenarios ??
  • IanMc Gregor Phenometric edge analysis
  • Katie McQuillan Assessing the Impact of Biodiversity on Forest Drought Resilience
  • Alexander Yoshizumi An Agent Based Model for Forecasting Land Cover Change in North Carolina

Thursday February 27

  • Vinicius Perin Estimating the cumulative hydrological impact of on-farm reservoirs using a watershed-scale model
  • Laura Tomkins Mesoscale snow band formation
  • Elyssa Collins Forecasting Urbanization Responses to Flooding Under Medium and High Emission Representative Concentration Pathways
  • Mollie Gaines Effects of climate and human drivers on surface water change
  • Thom Worm Mapping dark skies

Spring 2019 projects and papers

April 23:

  • Coffer,Megan: Rethinking the Florida bloom season: an investigation into cold-season cyanobacterial blooms
  • Gupta,Umesh: Pest or Pathogen Spread Simulation Optimization
    AIS data
  • Ifediora,Byron: Post-hurricane recovery assessment based on behavior models, socio-economic conditions and demographics
  • Inglis,Nicole: Spatially explicit urban-growth modeling in Northern Colorado’s dynamic WUI system
  • Karimi,Kimia: Weighted Regressions on Time, Discharge and Season
    Spatio-Temporal Optimization of Water Quality Monitoring Networks of Reservoirs Using Geostatistical Techniques and a Numerical Model
  • Liesch,Amanda: Visualization of Complex Soil Horizonation
  • Lin,Zekun: Simulating Population Growth and Urbanization Patterns under the Impacts of Sea Level Rise at Wilmington, NC
April 30:
  • Matli,Venkata: Effect of meteorological factors on Gulf Hypoxia
  • Millar,Garrett C: Humans, environment and emotions
  • Montgomery,Kellyn: Cut flower imports simulation for adaptive pest inspection strategies
    Crop surface analysis
  • Ricci,Shannon: Mapping underwater vessel noise propagation to assess acoustic pollution impact on natural soundscapes within the Florida Keys National Marine Sanctuary
  • Vivek Nanda,Vishnu Mahesh: Solar Potential Analysis of Parking lots and Roads in Raleigh
  • Wang,Ruixue: Using Social Media Data to Map Park Access
  • White,Corey: Impervious areas classification and change detection