WATERHYPERNET: a prototype network of automated in situ measurements of hyperspectral water reflectance for satellite validation and water quality monitoring

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.