Wide-Field-of-View Multispectral Camera Design for Continuous Turfgrass Monitoring

Lien Smeesters, Jef Verbaenen, Luca Schifano, Michael Vervaeke, Hugo Thienpont, Giancarlo Teti, Alessio Forconi, Filippo Lulli

Onderzoeksoutput: Articlepeer review

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Sustainably using resources, while reducing the use of chemicals, is of major importance in agriculture, including turfgrass monitoring. Today, crop monitoring often uses camera-based drone sensing, offering an accurate evaluation but typically requiring a technical operator. To enable autonomous and continuous monitoring, we propose a novel five-channel multispectral camera design suitable for integrating it inside lighting fixtures and enabling the sensing of a multitude of vegetation indices by covering visible, near-infrared and thermal wavelength bands. To limit the number of cameras, and in contrast to the drone-sensing systems that show a small field of view, a novel wide-field-of-view imaging design is proposed, featuring a field of view exceeding 164 degrees. This paper presents the development of the five-channel wide-field-of-view imaging design, starting from the optimization of the design parameters and moving toward a demonstrator setup and optical characterization. All imaging channels show an excellent image quality, indicated by an MTF exceeding 0.5 at a spatial frequency of 72 lp/mm for the visible and near-infrared imaging designs and 27 lp/mm for the thermal channel. Consequently, we believe our novel five-channel imaging design paves the way toward autonomous crop monitoring while optimizing resource usage.
Originele taal-2English
Pagina's (van-tot)1-18
Aantal pagina's18
Nummer van het tijdschrift5
StatusPublished - mrt 2023

Bibliografische nota

Funding Information:
The work was supported by the European Union’s Horizon2020, funded by ACTPHAST 4.0 project (grant agreement no 779472); Interreg (Fotonica Pilootlijnen, NWE758); Flanders Make; the Methusalem and Hercules foundations and the OZR of the Vrije Universiteit Brussel (VUB); and the ARTES 4.0 Consortium (advanced robotics and enabling digital technologies and systems 4.0) and Bando R&S 1 (grant agreement no 1.4_GREEN-i_Turf Europe Srl).

Publisher Copyright:
© 2023 by the authors.

Copyright 2023 Elsevier B.V., All rights reserved.


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