Floating Kelp Forest mapping using spaceborne Synthetic Aperture Radar on the British Columbia coast: the classification model

This dataset contains a machine learning model specifically designed to classify kelp, saved in the .sav format. It includes sample input data for the year 2017, covering the area of Malcolm Island, BC, Canada. Finally, to facilitate testing of the classification, a Jupyter notebook and a Miniconda environment definition were also included. The mask of the land, the sandy bottom substrate, and depths under 20 m, was not included in the bundle due to copyright of the input datasets. To obtain instructions on how to create your own mask file, please contact the Point of Contact, using provided email. <br>
This algorithm is the outcome of a research project funded by the Canadian Space Agency, as part of the Program to Support Research, Awareness, and Learning in Space Science and Technology, in collaboration with the Natural Sciences and Engineering Research Council of Canada Alliance grant.
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Details on the validation and development of the algorithm can be found in the associated peer-reviewed paper.