A Customisable Data Acquisition System for Open-Source Hyperspectral Imaging.

data acquisition hyperspectral imaging open-source remote sensing

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
21 Oct 2023
Historique:
received: 16 09 2023
revised: 17 10 2023
accepted: 17 10 2023
medline: 28 10 2023
pubmed: 28 10 2023
entrez: 28 10 2023
Statut: epublish

Résumé

Hyperspectral imagers, or imaging spectrometers, are used in many remote sensing environmental studies in fields such as agriculture, forestry, geology, and hydrology. In recent years, compact hyperspectral imagers were developed using commercial-off-the-shelf components, but there are not yet any off-the-shelf data acquisition systems on the market to deploy them. The lack of a self-contained data acquisition system with navigation sensors is a challenge that needs to be overcome to successfully deploy these sensors on remote platforms such as drones and aircraft. Our work is the first successful attempt to deploy an entirely open-source system that is able to collect hyperspectral and navigation data concurrently for direct georeferencing. In this paper, we describe a low-cost, lightweight, and deployable data acquisition device for the open-source hyperspectral imager (OpenHSI). We utilised commercial-off-the-shelf hardware and open-source software to create a compact data acquisition device that can be easily transported and deployed. The device includes a microcontroller and a custom-designed PCB board to interface with ancillary sensors and a Raspberry Pi 4B/NVIDIA Jetson. We demonstrated our data acquisition system on a Matrice M600 drone at a beach in Sydney, Australia, collecting timestamped hyperspectral, navigation, and orientation data in parallel. Using the navigation and orientation data, the hyperspectral data were georeferenced. While the entire system including the pushbroom hyperspectral imager and housing weighed 735 g, it was designed to be easy to assemble and modify. This low-cost, customisable, deployable data acquisition system provides a cost-effective solution for the remote sensing of hyperspectral data for everyone.

Identifiants

pubmed: 37896715
pii: s23208622
doi: 10.3390/s23208622
pmc: PMC10611323
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Australian Government
ID : IC170100023

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Auteurs

Yiwei Mao (Y)

School of Physics, The University of Sydney, Sydney, NSW 2006, Australia.
ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia.

Christopher H Betters (CH)

School of Physics, The University of Sydney, Sydney, NSW 2006, Australia.
ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia.

Samuel Garske (S)

ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia.

Jeremy Randle (J)

Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006, Australia.

K C Wong (KC)

ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia.

Iver H Cairns (IH)

School of Physics, The University of Sydney, Sydney, NSW 2006, Australia.
ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia.

Bradley J Evans (BJ)

ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia.
School of Environment and Rural Science, University of New England, Armidale, NSW 2351, Australia.

Classifications MeSH