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Preprint - A Particle Swarm Optimization based Approach to Pre-tune Programmable Hyperspectral Sensors.pdf (1.15 MB)
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A Particle Swarm Optimization based Approach to Pre-tune Programmable Hyperspectral Sensors

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preprint
posted on 21.02.2021, 16:03 by Bikram BanerjeeBikram Banerjee, Simit Raval
This article presents development of an innovative approach to identify spectrally significant wavelength bands, for a given environment, to tune hyperspectral sensor acquisition before UAV borne surveys. As several programmable hyperspectral sensors are now available, it is often a challenge to consider the suitable wavelengths of interest. Researchers often conduct a thorough field survey to identify the composition of target endmembers in an area to identify suitable wavelengths before UAV survey, which is difficult and cumbersome. Otherwise, the selection of wavelengths by trial-and-error is error-prone.
To our knowledge, this is the first time a technique for optimal hyperspectral band (or feature) selection has been proposed to pre-tune UAV-hyperspectral sensors before the survey. A metaheuristic evolutionary workflow using Particle Swarm Optimisation was used for this. The method is easy in the field and efficient to identify optimal bands before UAV-hyperspectral surveys.

History

Email Address of Submitting Author

bikram.banerjee@agriculture.vic.gov.au

ORCID of Submitting Author

0000-0002-5542-3751

Submitting Author's Institution

Agriculture Victoria

Submitting Author's Country

Australia