By: Christine Dybwad, UiT.
Remote sensing, particularly through imaging spectroscopy, offers a new tool in this effort, enabling monitoring and targeted assessment of these regions. By producing higher-quality datasets at lower costs, this technology is now a step closer to a wider accessibility.
The hyperspectral imaging from satellites facilitates a higher resolution characterization and identification of the pigment composition of algal blooms observed. A known pigment composition opens for the identification of key groups like toxic algae, kelp growth, and the timing of specific algal blooms. Possibilities for monitoring at this level with remote sensing can be of great importance for both fish farmers, as well as coastal and ocean management. Obstacles in georeferencing have challenged such observations in environments where satellite signals are compromised but have now been overcome and facilitate georeferenced data from the images.
On August 21st, Master of Science Oliver Kevin Hasler successfully defended his PhD entitled “Hyperspectral remote sensing and navigation in coastal environments using UAVs”. Dr. Hasler’s thesis demonstrates how an effective airborne imaging spectroscopy system, specifically for hyperspectral imaging, can be assembled using commercially available off-the-shelf components and deployed on cost-effective small unmanned aerial vehicles (UAVs).
Hasler defending his thesis. Photo: Yongmei Gong.
His work demonstrates that it is feasible to construct an affordable and effective airborne hyperspectral imaging system using commercially available off-the-shelf components, which can be deployed on small, inexpensive unmanned aerial vehicles (UAVs). The thesis explores the adaptation of this technology for various applications, including ocean color mapping, and addresses challenges related to data quality, georeferencing, and navigation in environments where satellite signals are compromised.
Key aspects of the thesis include designing the imaging system, operational considerations for data quality, calibration of the imaging spectrometer, and special attention to georeferencing hyperspectral and RGB data using a specific algorithm. This allows for directly georeferenced data from the mounted hyperspectral imager. Overall, the thesis aims to democratize hyperspectral imaging technology, making it accessible for a wider range of applications and users by reducing costs and improving navigation reliability in challenging environments.
Dr. Oliver Kevin Hasler (center-right) with his supervisors and opponents. Photo: Yongmei Gong.
Oliver Kevin Hasler, who is at the Department of Engineering Cybernetics at NTNU, was supervised by Professor Torleiv Håland Bryne and Professor Tor Arne Johansen, both at NTNU. His evaluation committee consisted of Professor Maarja Kuusmaa (biorobotics) from Tallinn University of Technology in Estonia, and Associate Professor Bradly Evans (remote sensing) from University of New England in Australia