Remote sensing reflectance (Rrs)
The primary field measurement for calibration and validation of Rrs is above- or in-water radiometry (henceforth radiometry) measurements. Recent advances in sensor technology have resulted in wider availability of these instruments (see Section 2.3.3), and efforts have been made to develop networks of radiometry installations (i.e., AeroNET) to support calibration and validation of satellite-based Rrs measurements. In addition, the availability of these sensors has enabled research groups to include these measurements in the suite of field parameters collected during field campaigns. However, cost, computing capability, and technical expertise limitations still exist, leading to gaps in the availability of radiometry datasets.
In addition, ensuring that field radiometry measurements are obtained under optimal conditions continues to be challenging in coastal and inland waters. Considerations include spatiotemporal variability in illumination conditions, optical variability of the water bodies of interest, and atmospheric conditions. As such, radiometry validation data needs to capture: a) different solar zenith and azimuthal angles encountered at different times of the year and/or latitudes; b) optical variability representative of the diversity in environmental conditions within or across waterbodies; and c) observations across different atmospheric states and aerosol influences, under varying degrees of adjacency effects. The sampling approach thus depends on the application, and waterbodies of interest, and specifications of the satellite sensor(s) to be used.
Data quality can be ensured by following standard operating procedures (such as Simis et al., 2012) and maintaining optimal viewing geometries (IOCCG protocol). Planning sampling times to be near-coincident with the satellite overpass areis encouraged. Recent studies focusing on inland or coastal waters have used matchup windows of +/- 3 hours (e.g., Bailey & Werdell, 2006; Vanhellemont, 2019; Wang et al. 2019; Maciel & Pedocchi, 2022; Sòria-Perpinyà et al. 2022), while others selected a larger window for inland waters, often +/- 24 hours (Warren et al. 2019; Pahlevan et al., 2021). To select a reasonable temporal window, it is critical to consider the spatiotemporal dynamics in the validation location for a given system and season (see Section 3.2).
Furthermore, factors affecting uncertainty in field radiometry measurements should be recorded and considered. Naturally occurring changes in water constituents and illumination conditions can be accounted for in the in situ data throughby replicating measurements over a short period of time (in the scale of minutes, e.g., Vanhellemont, 2020; Cazzaniga & Zibordi, 2023). Systematic errors (biases) may be introduced by the sensors themselves, and can be reduced by ensuring proper sensor set-up, calibration, and routine cleaning of the fore optics (Ruddick et al., 2019). Basic statistics on the data, including mean, standard deviation, percentiles, and number of samples, should be reported (Lehmann et al., 2023). In addition, ancillary data such as a) changing illumination conditions reported as cloud fraction, information on viewing geometry, and, optionally, photos of the sky in the cardinal directions; b) potential for bottom reflectance based on the first optical or Secchi depth and water depth; c) distance from shore to assess adjacency effects (Bulgarelli & Zibordi, 2018; see also Section 3.3.2); d) sea state (wave height; surface roughness) estimated in the field or through the wind speed (Zibordi, 2016); and e) instrument self-shading (Gordon & Ding, 1992; Zibordi & Ferrari, 1995) and shading and reflectance from the deployment platform (Hooker & Zibordi, 2005; Talone & Zibordi, 2019), should be reported.
Practical needs include advancing the understanding of the advantages and disadvantages of different system and sensor set-ups for inland and coastal waters, hands-on training on sensor set-up and data acquisition, and walk-throughs of different data processing options and uncertainty measures. Easy and practical ways to check the calibration of sensors in the field can help identify instrument issues at the time ofduring data collection. More information and studies of the severity of the impacts of known issues (e.g., adjacency effects, shading, and reflectance from the deployment platform) on radiometric measurements in inland and coastal water settings and associated satellite sensors (as opposed to oceanic settings and ocean color satellite sensors), can help minimize them.
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