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Using Remote Sensing Data to Model Sand Dune Complexes

Project Full Title:

Using Remotely Sensed Imagery from Drones to Model the Topography and Vegetation of West Michigan Sand Dune Complexes

Project Mentor(s):

Stephenson,Darin

Project Mentor(s) EMail:

stephenson@hope.edu

Project Start Date:

5/13/2019

Project End Date:

7/24/2019

Project Description:

This interdisciplinary project will incorporate the disciplines of Mathematics, Ecology, and Computer Science. However the project is specifically housed within the Hope College Department of Mathematics.

Coastal sand dune complexes are topographically and ecologically diverse, with land forms ranging from actively developing to stable, and surfaces ranging from bare sand to densely vegetated. Vegetation often ranges from open grasslands to mature forest, and interactions among waves, wind, surface topography, and vegetation make dune landscapes highly dynamic. Remote sensing using drones is an efficient way to map changes in dune vegetation and topography, but resulting imagery must be processed and classified. To map surface topography, ground points must be separated from vegetation points before models of the ground surface are constructed. Classification should also distinguish different types of plants and even different species. This project will use machine learning to classify points in remotely sensed imagery of sand dune complexes. The classified points will be used to construct maps of topography and vegetation that will be used to monitor ecological and topographic change for scientific and management applications.

Preferred student background includes Linear Algebra and Multivariate Calculus (Math 231-232 at Hope College) and some computer programming experience. Various software packages will be employed in the summer combined with the R statistical package and some Python programming.

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