Paper
30 August 2023 Research progress in unmanned aerial vehicle-borne hyperspectral imaging payload
Shuangxing Ju, Jinlin Zou, Ruibo Ma
Author Affiliations +
Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 1279723 (2023) https://doi.org/10.1117/12.3007374
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China
Abstract
Hyperspectral imaging payloads are widely employed in diverse applications, including geological surveys, plant research, resource exploration, and more. Despite the emergence of spaceborne hyperspectral imaging, airborne imagers remain crucial in remote sensing due to their superior performance capabilities. This article offers a comprehensive review of hyperspectral imaging payload development and application across various platforms and instruments, with a specific focus on the limitations of unmanned aerial vehicle-borne platforms. Ultimately, this research points out there are several challenges that need to be addressed in future studies and presents an outlook of challenges and future trends. This article also assists researchers in quickly gaining an overview of the existing vast literature in the related fields.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Shuangxing Ju, Jinlin Zou, and Ruibo Ma "Research progress in unmanned aerial vehicle-borne hyperspectral imaging payload", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 1279723 (30 August 2023); https://doi.org/10.1117/12.3007374
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KEYWORDS
Unmanned aerial vehicles

Hyperspectral imaging

Image processing

Imaging systems

Satellites

Image transmission

Data processing

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