Lake SkyWater—A Portable Buoy for Measuring Water-Leaving Radiance in Lakes Under Optimal Geometric Conditions

This study introduces Lake SkyWater (LSW), a novel radiometric buoy designed for the reliable measurement of remote sensing reflectance (R<sub>rs</sub>) in lakes using the Skylight-Blocked Approach (SBA). LSW addresses key challenges in "on-water" field radiometry owing to its motorised rotating system, which maintains the radiance sensor in optimal geometrical conditions (i.e., facing the sun). Our device is easy to transport and deploy and can be controlled with a smartphone over Wi-Fi. Its modular design, which uses standard components and custom 3D-printed parts, facilitates customisation. A field experiment demonstrated excellent performance in the visible spectrum (400-700 nm) and no significant differences compared with handheld SBA measurements when measuring R<sub>rs</sub> (coefficient of determination > 0.99 and general accuracy (median symmetric accuracy) of ~2.43%). Areas for potential improvement were identified, such as refinement of orientation control and addressing the occasional rotation of the float. Nonetheless, LSW shortens the acquisition time, reduces the risk of fore-optics contamination, and ensures that the measurements are conducted under optimal geometric conditions. In conclusion, LSW is a promising instrument for the operational collection of high-quality R<sub>rs</sub> spectra in lakes, which is important for advancing both research and monitoring applications in aquatic remote sensing.

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Publication Details

Journal
Sensors
Published
2025-02-28
DOI
https://doi.org/10.3390/s25051525
Citations
2
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
1.63
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article

Lake SkyWater—A Portable Buoy for Measuring Water-Leaving Radiance in Lakes Under Optimal Geometric Conditions

Arthur Coqué, T. Tormos, Jean-Michel Martínez, Tiphaine Peroux et al.
2 citations
Sensors
Water Quality Monitoring Technologies
1.63
article

Lake SkyWater—A Portable Buoy for Measuring Water-Leaving Radiance in Lakes Under Optimal Geometric Conditions

Arthur Coqué, T. Tormos, Jean-Michel Martínez, Tiphaine Peroux, Guillaume Morin
article en
2 citations

Abstract

This study introduces Lake SkyWater (LSW), a novel radiometric buoy designed for the reliable measurement of remote sensing reflectance (R<sub>rs</sub>) in lakes using the Skylight-Blocked Approach (SBA). LSW addresses key challenges in "on-water" field radiometry owing to its motorised rotating system, which maintains the radiance sensor in optimal geometrical conditions (i.e., facing the sun). Our device is easy to transport and deploy and can be controlled with a smartphone over Wi-Fi. Its modular design, which uses standard components and custom 3D-printed parts, facilitates customisation. A field experiment demonstrated excellent performance in the visible spectrum (400-700 nm) and no significant differences compared with handheld SBA measurements when measuring R<sub>rs</sub> (coefficient of determination > 0.99 and general accuracy (median symmetric accuracy) of ~2.43%). Areas for potential improvement were identified, such as refinement of orientation control and addressing the occasional rotation of the float. Nonetheless, LSW shortens the acquisition time, reduces the risk of fore-optics contamination, and ensures that the measurements are conducted under optimal geometric conditions. In conclusion, LSW is a promising instrument for the operational collection of high-quality R<sub>rs</sub> spectra in lakes, which is important for advancing both research and monitoring applications in aquatic remote sensing.

SensorsVol. 25(5)
Centre National de la Recherche Scientifique (FR), Aix-Marseille Université (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Géosciences Environnement Toulouse (FR), Magellium (France) (FR), Institut de Recherche pour le Développement (FR)
Clean water and sanitation
Openalex Percentile: Top 18%
Water Quality Monitoring Technologies
1.63
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