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Article

From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones

by
Oliver Hasler
1,*,
Håvard S. Løvås
2,
Adriënne E. Oudijk
1,
Torleiv H. Bryne
1 and
Tor Arne Johansen
1
1
Department of Engineering Cybernetics, Norwegian University of Science and Technology, NTNU, 7034 Trondheim, Norway
2
Department of Biology, Norwegian University of Science and Technology, NTNU, 7491 Trondheim, Norway
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(17), 3202; https://doi.org/10.3390/rs16173202
Submission received: 2 May 2024 / Revised: 18 July 2024 / Accepted: 15 August 2024 / Published: 29 August 2024
(This article belongs to the Section Engineering Remote Sensing)

Abstract

This paper presents an innovative, holistic, and comprehensive approach to drone-based imaging spectroscopy based on a small, cost-effective, and lightweight Unmanned Aerial Vehicle (UAV) payload intended for remote sensing applications. The payload comprises a push-broom imaging spectrometer built in-house with readily available Commercial Off-The-Shelf (COTS) components. This approach encompasses the entire process related to drone-based imaging spectroscopy, ranging from payload design, field operation, and data processing to the extraction of scientific data products from the collected data. This work focuses on generating directly georeferenced imaging spectroscopy datacubes using a Do-It-Yourself (DIY) imaging spectrometer, which is based on COTS components and freely available software and methods. The goal is to generate a remote sensing reflectance datacube that is suitable for retrieving chlorophyll-A (Chl-A) distributions as well as other properties of the ocean spectra. Direct georeferencing accuracy is determined by comparing landmarks in the directly georeferenced datacube to their true location. The quality of the remote sensing reflectance datacube is investigated by comparing the Chl-A distribution on various days with in situ measurements and satellite data products.
Keywords: imaging spectroscopy; hyperspectral imaging; UAV; remote sensing imaging spectroscopy; hyperspectral imaging; UAV; remote sensing

Share and Cite

MDPI and ACS Style

Hasler, O.; Løvås, H.S.; Oudijk, A.E.; Bryne, T.H.; Johansen, T.A. From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones. Remote Sens. 2024, 16, 3202. https://doi.org/10.3390/rs16173202

AMA Style

Hasler O, Løvås HS, Oudijk AE, Bryne TH, Johansen TA. From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones. Remote Sensing. 2024; 16(17):3202. https://doi.org/10.3390/rs16173202

Chicago/Turabian Style

Hasler, Oliver, Håvard S. Løvås, Adriënne E. Oudijk, Torleiv H. Bryne, and Tor Arne Johansen. 2024. "From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones" Remote Sensing 16, no. 17: 3202. https://doi.org/10.3390/rs16173202

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