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This paper describes a prototype network of automated in situ measurements of hyperspectral water reflectance suitable for satellite validation and water quality monitoring. Radiometric validation of satellite-derived water reflectance is essential to ensure that only reliable data, e.g., for estimating water quality parameters such as chlorophyll a concentration, reach end-users. Analysis of the differences between satellite and in situ water reflectance measurements, particularly unmasked outliers, can provide recommendations on where satellite data processing algorithms need to be improved. In a massively multi-mission context, including Newspace constellations, hyperspectral missions and missions with broad spectral bands not designed for “water colour”, the advantage of hyperspectral over multispectral in situ measurements is clear. Two hyperspectral measurement systems, PANTHYR (based on the mature TRIOS/RAMSES radiometer) and HYPSTAR® (a newly designed radiometer), have been integrated here in the WATERHYPERNET network with SI-traceable calibration and characterisation. The systems have common data acquisition protocol, data processing and quality control. The choice of validation site and viewing geometry and installation considerations are described in detail. Three demonstration cases are described: 1. PANTHYR data from two sites are used to validate Sentinel-2/MSI (A&B); 2. HYPSTAR® data at six sites are used to validate Sentinel-3/OLCI (A&B); 3. PANTHYR and HYPSTAR® data in Belgian North Sea waters are used to monitor phytoplankton parameters, including Phaeocystis globosa, over two 5 month periods. Conclusion are drawn regarding the quality of Sentinel-2/MSI and Sentinel-3/OLCI data, including indications where improvements could be made. For example, a positive bias (mean difference) is found for ACOLITE_DSF processing of Sentinel-2 in clear waters (Acqua Alta) and clues are provided on how to improve this processing. The utility of these in situ measurements, even without accompanying hyperspectral satellite data, is demonstrated for phytoplankton monitoring. The future evolution of the WATERHYPERNET network is outlined, including geographical expansion, improvements to hardware reliability and to the measurement method (including uncertainty estimation) and plans for daily distribution of near real-time data.

Validation of water reflectance using in situ data is essential to ensure the quality of ocean colour satellite-derived products useful for water quality monitoring, like turbidity and chlorophyll-a concentration. Since December 2021, the HYPERNETS automated hyperspectral system has been collecting data in the optically complex and highly turbid waters of the Río de la Plata, an ideal scenario for testing atmospheric correction algorithms’ performance. The site, located 60 km south of Buenos Aires (Argentina), is described in relation to the water reflectance spectral features and variability using high spatial resolution imagery and a methodology is proposed to objectively select a sensor-specific location of a reference pixel for satellite validation. Six months of data is used to evaluate surface water reflectance operational products from multi-spectral systems like Landsat 8&9/OLI (L89/OLI), Sentinel-2/MSI (S2/MSI) & Sentinel-3/OLCI (S3/OLCI), and PlanetScope SuperDoves (PS/SD), and also non standard products for Aqua/MODIS (Aqua/MODIS) and SNPP&JPSS1/VIIRS (SJ/VIIRS) missions. Moreover, the standard surface water reflectance product from the hyperspectral PRISMA mission could also be evaluated. The matchups show general good results when in situ measurements are compared to L2 standard products of high spatial resolution sensors that use land-based atmospheric correction approach, if sun glint contamination is avoided. Low mean relative percentage difference was found for S2/MSI (2.45%) and L89/OLI (−3.52%), but higher for PS/SD (30.7%). In turn, S3/OLCI medium resolution also showed low mean relative differences (2.31%), while SJ/VIIRS and Aqua/MODIS showed larger and negative differences (−16.35 for SJ/VIIRS and −35.6% for Aqua/MODIS) which showed a clear increase towards the shortest blue bands. The results show the great potential of the HYPERNETS automated system to provide high quality and quantity of data for validation of satellite data at all visible and near infrared (VNIR, 400–900 nm) wavelengths in a multi-mission perspective.

The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented.