Published June 19, 2023 | Version 1.2
Dataset Open

Initial Sample of HYPERNETS Hyperspectral Water Reflectance Measurements for Satellite Validation at Berre coastal lagoon, BEFR site (France)

  • 1. LOV CNRS/SU UMR7093

Contributors

Data manager:

Project leader:

  • 1. RBINS

Description

The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site at Etang de Berre in France (BEFR). It is a subset of the complete data record which consists of the best quality BEFR measurements which could be used for satellite validation. 

The provided NetCDF files are the L2A hypernets products with water leaving radiance and reflectances, with and without NIR Similarity Correction (see Ruddick et al., 2006, DOI:10.2307/3841124). The reflectance in the L2A products is the Water Reflectance without NIR Similarity Correction (referred to as reflectance_nosc in the file) defined as:

ρwnosc=π(LuρFLd)/Ed

 

where Lu is the upwelling radiance (at 40° zenith angle, and, 90° or 135° azimuth angle relative to the sun), Ld is the downwelling radiance (at 140° zenith angle, and, 90° or 135° azimuth angle relative to the sun). Ed is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance).

For the BEFR site, the reflectance corrected for the NIR Similarity correction (epsilon, see Ruddick et al., 2006) is also provided:

ρw=π(LuρFLd)/Edϵ

 

These reflectances have dimensions of wavelength and series, where each series is a set of measurements for the computation of a water reflectance measurement. In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.

The HYPSTAR®-SR (Standard Range) instruments deployed at each land HYPERNETS site consist of a VNIR sensor and autonomously collect data between 380-1000 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm. The hypernets_processor (Goyens et al. 2021, DOI: 10.1109/IGARSS47720.2021.9553738; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. The current dataset is limited to the 400-900 nm range. Uncertainties are not yet included.

To obtain this dataset, we start from the full BEFR data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to supply the best quality data suitable for satellite validation:

1. The coefficient of variation in water reflectance is below 10% in the 500-600 nm range

2. The water reflectance (after correction for the NIR similarity) between 700-900 nm is below 0.01

Notes

HYPERNETS project is funded by Horizon 2020 research and innovation program, Grand Agreement No 775993.

Files

HYPERNETS_BEFR_L2A_REF_v1.2.zip

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Additional details

Funding

HYPERNETS – A new hyperspectral radiometer integrated in automated networks of water and land bidirectional reflectance measurements for satellite validation 775983
European Commission

References

  • Ruddick et al., 2006, DOI:10.2307/3841124
  • Goyens et al. 2021, DOI: 10.1109/IGARSS47720.2021.9553738