Australian aquatic bio-optical dataset with applications for satellite calibration, algorithm development and validation

Drayson, Nathan; Anstee, Janet; Botha, Elizabeth C.; Kerrisk, Gemma; Ford, Phillip W.; Wojtasiewicz, Bożena; Clementson, Lesley; McLaughlin, M. J.; Hutton, Marlee

doi:10.1016/j.dib.2022.108489

Cited by 2 publications

(2 citation statements)

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“…The first case study is of a hypothetical cyanobacterial bloom representative of Lake Hume, a large drinking and agricultural water reservoir located in southeastern Australia [ 21 ]. The IOPs and R rs at Lake Hume have been characterized by previous field measurements [ 22 ]. Here, we demonstrate the retrieval of chl- a pigment.…”

Section: Methodsmentioning

confidence: 99%

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Demonstration of a Modular Prototype End-to-End Simulator for Aquatic Remote Sensing Applications

Matthews,

Dekker,

Price

et al. 2023

Sensors

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This study introduces a prototype end-to-end Simulator software tool for simulating two-dimensional satellite multispectral imagery for a variety of satellite instrument models in aquatic environments. Using case studies, the impact of variable sensor configurations on the performance of value-added products for challenging applications, such as coral reefs and cyanobacterial algal blooms, is assessed. This demonstrates how decisions regarding satellite sensor design, driven by cost constraints, directly influence the quality of value-added remote sensing products. Furthermore, the Simulator is used to identify situations where retrieval algorithms require further parameterization before application to unsimulated satellite data, where error sources cannot always be identified or isolated. The application of the Simulator can verify whether a given instrument design meets the performance requirements of end-users before build and launch, critically allowing for the justification of the cost and specifications for planned and future sensors. It is hoped that the Simulator will enable engineers and scientists to understand important design trade-offs in phase 0/A studies easily, quickly, reliably, and accurately in future Earth observation satellites and systems.

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Section: Methodsmentioning

confidence: 99%

“…A four-component bio-optical model was used to model the inherent optical properties of water, which included water, phytoplankton, NAPs, and CDOM. The SIOPs for NAPs and

were generated from average values of 55 measurements at Lake Hume [ 22 ]. The chl- a -specific SIOPs for the cyanobacterium Microcystis aeruginosa were used [ 33 ].…”

Section: Table A1mentioning

confidence: 99%