Speaker
Sarah Day
(William & Mary)
Description
This talk focuses on the use of cubical homology and topological persistence as a framework for pattern quantification and image processing. As illustration, we will discuss a study that applies these methods to noisy spatial population data generated by a coupled-patch model to mimic grey scale satellite images of vegetation. Early work shows promise in detecting early warning signals of collapse as well as automating image processing techniques for noise reduction.
Author
Sarah Day
(William & Mary)
Co-authors
Alethea Callahan
(William & Mary)
Laura Storch
(Bates College)