Publications | Institutes | Persons | Datasets | Projects | Maps | ||||
PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2022
Citation
Vansteenwegen, D.; Vanhellemont, Q.; Flanders Marine Institute (VLIZ): Belgium; Royal Belgian Institute for Natural Sciences (RBINS): Belgium; (2024): PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2022. Marine Data Archive. https://marineinfo.org/id/dataset/8495
Contact:
Vanhellemont, Quinten Availability: This dataset is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Notes: If you use the data provided by PANTHYR, please refer to it in any of your publications as: "This work was supported by PANTHYR data & infrastructure provided by the Flanders Marine Institute (VLIZ) and Royal Belgian Institute for Natural Sciences (RBINS)".
Description
Autonomously acquired above-water PANTHYR water reflectance data from a pair of TriOS RAMSES radiance and irradiance sensors, details provided in Vansteenwegen et al. 2019. Data passed automated quality control but has not been screened by an expert. moreThis dataset contains autonomously acquired abovewater PANTHYR water reflectance data from a pair of TriOS RAMSES radiance and irradiance sensors. Measurements are performed under a sun-sensor geometry that minimises sun and sky glint on the air-water interface, as recommended by Mobley (1999), and utilised commonly in above water measurements, e.g. by Ruddick et al. (2006). Irradiance and radiance measurements are made sequentially rather than simultaneously, with a full cycle containing 3 irradiance (Ed), 3 downwelling radiance (Ld), 11 upwelling radiance (Lu), 3 more Ld and 3 more Ed. This sequence takes about 1 minute to complete in normal illumination conditions, and temporal stability checks are performed on these sequential measurements (Vanhellemont 2020). A given number of valid measurements (Ed: 5/6, Ld: 5/6, Lu: 9/11) are required for further processing. RAMSES data are resampled to a common wavelength grid between 355 and 945 nm with a 2.5 nm step. A "Fresnel" correction for the air-water interface reflectance is performed using the Mobley (1999) LUT for a fixed (2 m/s) or modeled (NCEP) wind speed. Full details on the PANTHYR system are provided in Vansteenwegen et al. 2019. This dataset contains the average and standard deviation of hyperspectral irradiance (ed), downwelling radiance (ld), total upwelling radiance (lu), and derived water-leaving radiance (lw). Water-leaving radiance reflectance is provided with NIR similarity spectrum correction (rhow) and without NIR similarity spectrum correction (rhow_nosc). Data passed automated quality control but have not been screened by an expert. The general objective of the HYPERMAQ project was to develop and test new algorithms for aquatic remote sensing of coastal and inland waters, using both hyperspectral and high resolution multispectral satellite data to provide more than “just” concentration of suspended particulate matter and chlorophyll. Test sites focused particularly on turbid waters. The PANTHYR (pan-and-tilt hyperspectral radiometer system) was designed in HYPERMAQ for autonomous measurement of hyperspectral water reflectance for the validation of satellite reflectance in visible and near-infrared bands (400–900 nm). Scope Themes: Physical > Optical measurements Keywords: Air-water interface, Hyperspectral imaging, Irradiance, Optical remote sensing, Radiance, Radiometry, Reflectance, Remote sensing, Remote sensing techniques, Research platform, ANE, North Sea Geographical coverage ANE, North Sea [Marine Regions] Temporal coverage
25 January 2022 - 16 November 2022 Parameter
Irradiance Contributors
Related datasets
Other relation: PANTHYR hyperspectral water reflectance - O1BE, more Project
HYPERMAQ: Hyperspectral and multi-mission high resolution optical remote sensing of aquatic environments, more
Publication
Based on this dataset
Hieronymi, M. et al. (2023). Ocean color atmospheric correction methods in view of usability for different optical water types. Front. Mar. Sci. 10: 1129876. https://dx.doi.org/10.3389/fmars.2023.1129876, more
Lavigne, H. et al. (2023). Turbid water sun glint removal for high resolution sensors without SWIR, in: Bostater, C.R. et al. Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions, 2023, 3 - 6 September 2023, Amsterdam, Netherlands. Proceedings of SPIE, the International Society for Optical Engineering, : pp. 1272804, more
Vanhellemont, Q. (2023). Evaluation of eight band SuperDove imagery for aquatic applications. Optics Express 31(9): 13851-13874. https://dx.doi.org/10.1364/oe.483418, more
Dierssen, H.M. et al. (2022). QWIP: A quantitative metric for quality control of aquatic reflectance spectral shape using the Apparent Visible Wavelength. Front. Remote Sens. 3: 869611. https://dx.doi.org/10.3389/frsen.2022.869611, more
Lavigne, H.; Ruddick, K.; Vanhellemont, Q. (2022). Monitoring of high biomass Phaeocystis globosa blooms in the Southern North Sea by in situ and future spaceborne hyperspectral radiometry. Remote Sens. Environ. 282: 113270. https://dx.doi.org/10.1016/j.rse.2022.113270, more
Vanhellemont, Q. (2020). Sensitivity analysis of the dark spectrum fitting atmospheric correction for metre- and decametre-scale satellite imagery using autonomous hyperspectral radiometry. Optics Express 28(20): 29948. https://dx.doi.org/10.1364/oe.397456, more
Used in this dataset
Vansteenwegen, D. et al. (2019). The Pan-and-Tilt Hyperspectral Radiometer system (PANTHYR) for autonomous satellite validation measurements—prototype design and testing. Remote Sens. 11(11): 1360. https://dx.doi.org/10.3390/rs11111360, more
URLs
Dataset status: Completed
Data type: Data
Data origin: Sensor platform
Metadatarecord created: 2024-02-29
Information last updated: 2024-02-29
|