Sea-Ice Floe Segmentation

• Main Author: Denton, Alexis Anne
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Zenodo 2022
• Subjects: Sea Ice; Remote Sensing; Arctic; Canada; canada basin; Sea ice
• Online Access: https://dx.doi.org/10.5281/zenodo.6146145; https://zenodo.org/record/6146145

This repository contains a user-friendly, MATLAB Live Script to easily and automatically segment sea ice floes (chunks) in imagery (for example, from satellites or aerial platforms). The algorithm and code were written by Alexis Denton (Yale University) for and used to segment high-resolution optical satellite images in the accompanying submitted manuscript (preprint, in review) coauthored with Mary-Louise Timmermans (Yale University), Denton and Timmermans (2021) (https://doi.org/10.5194/tc-2021-368). This algorithm was developed to contribute an easy, automated, and reproducible method to the Arctic science community for the identification of sea ice floes in remote sensing imagery. If you use this algorithm in your work or research or for any other reason, credit the author here (Alexis Denton) and cite the code DOI issued by Zenodo. The DOI badge to the right points to the latest released version of the repository. The development of this code and the research presented in the manuscript was funded by the Office of Naval Research as a part of their Multi-University Research Initiative (MURI) Mathematics and Data Science for Physical Modeling and Prediction of Sea Ice. To learn more about the work of the Sea Ice MURI, please visit https://seaicemuri.org/. For further details about the algorithm, please see Denton and Timmermans (2021). Version 0.1.0-alpha Note: This is a pre-release of Sea-Ice Floe Segmentation. : {"references": ["Denton, A. A. and Timmermans, M.-L.: Characterizing the Sea-Ice Floe Size Distribution in the Canada Basin from High-Resolution Optical Satellite Imagery, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-368, in review, 2021."]}