Mapping Marine Macroalgae along the Norwegian Coast Using Hyperspectral UAV Imaging and Convolutional Nets for Semantic Segmentation
Permanent link
https://hdl.handle.net/10037/31681Date
2023-10-20Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Skjelvareid, Martin Hansen; Rinde, Eli; Hancke, Kasper; Blix, Katalin; Hoarau, Galice GuillaumeAbstract
Marine macroalgae form underwater "blue forests" with several important functions. Hyperspectral imaging from unmanned aerial vehicles provides a rich set of spectral and spatial data that can be used to map the distribution of such macroalgae. Results from a study using 81 annotated hyper-spectral images from the Norwegian coast are presented. A U-net convolutional network was used for classification, and accuracies for all macroalgae classes were above 90%, indicating the potential of the method as an accurate tool for blue forest monitoring.
Publisher
IEEECitation
Skjelvareid, Rinde, Hancke, Blix, Hoarau. Mapping Marine Macroalgae along the Norwegian Coast Using Hyperspectral UAV Imaging and Convolutional Nets for Semantic Segmentation. IEEE International Geoscience and Remote Sensing Symposium proceedings. 2023Metadata
Show full item record
Copyright 2023 The Author(s)