Topological Segmentation and Tracking for Space Weather Modeling
Divya Banesh, Natalie Klein, Steven K. Morley, Ayan K. Biswas, Vania Koleva Jordanova, Michael Henderson, Earl Lawrence · 2021 IEEE International Conference on Big Data (Big Data) · 2021
The segmentation and temporal tracking of fast flow structures called bursty bulk flows is an integral part of space weather study. This paper presents the first known topological segmentation and tracking technique to analyze bursty bulk flows. We apply contour tree-based segmentation to identify regions of high plasma velocity from data output from space weather simulations. We then employ a Kuhn-Munkers assignment algorithm with a modified Wasserstein metric to match features in adjacent time steps. A newly implemented algorithm to determine splits and merges of segments results in a fully topological framework for feature detection and tracking of fast flow channels.