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Onboard Hyperspectral Classification Enables Georeferencing

Langer, Dennis David; Garrett, Joseph Landon; Birkeland, Roger; Berg, Simen; Orlandic, Milica
Journal article, Peer reviewed
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WHISPERS_2023_paper_89_chiatante.pdf (3.034Mb)
URI
https://hdl.handle.net/11250/3122416
Date
2023
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Original version
2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)   10.1109/WHISPERS61460.2023.10430746
Abstract
The Norwegian University of Science and Technology (NTNU) has been building a system composed of multiple remote sensing agents for ocean observations. NTNU launched the first HYPerspectral Smallsat for Ocean observation (HYPSO-1) satellite on the 13 th of January 2022, adding a Hyperspectral Imager satellite to its disposal, while HYPSO-2 will be launched in 2024. However, due to the high dimensionality of the collected data, onboard processing has been introduced on the satellite to potentially deliver information in a more rapid and condensed manner. In this paper, the operational use of onboard classification will be explored, investigating how different algorithms can be applied for data reduction to potentially enable decision-making onboard the satellite such as the use of classified images for onboard georeferencing. The classification could be used to enable near real-time data latency cooperation between the satellite and the other agents, such as autonomous surface vehicles for in-situ measurements.
Publisher
IEEE
Journal
Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Copyright
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

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