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4.4 How to estimate aquatic ecosystem variables from water leaving radiance or reflectance using in-water algorithms (optically deep and optically shallow waters).

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4.5 In-situ measurements for algorithm development and calibration designed to make optimal use of the proposed sensor(s).

4.6 Instrumentation and campaign requirements for validation.

4.2 Atmospheric correction methods

Atmospheric correction is the inversion of radiative transport models that characterise the

atmospheric optical properties in various degrees of detail. This correction is necessary to obtain the bottom of atmosphere (BOA) or surface reflectance or water leaving radiance of imaged water pixels. Pixels that are contaminated by dense smoke, fog, clouds or cloud shadows need to be filtered out prior to atmospheric correction. As seen in Chapter 2 of this report, the aquatic ecosystem main radiative transport processes are influenced by the aquatic optical active

components, the substratum or benthic vegetation reflectances and pure water itself. In the case of floating plants or floating algae their reflectance is the sought after parameter. The atmosphere needs characterising as follows:

• Absorption by absorbing aerosols and gasses (O2, O3, NO2 and H2O)

• Rayleigh scattering by small molecules of non-absorbing atmospheric gasses (CO, N2O, CH4 and CO2)

• Mie scattering by larger molecules (aerosols and water vapour) • Polarization effects

In addition to this, scattering by ice crystals in partially transparent cirrus clouds and aircraft contrails, lens effects at cloud edges and “the adjacency effect” have an influence of the observed TOA signal of a water pixel. Depending on location, time and topographical height, different mixtures of atmospheric optical active components and variable path lengths lead to different effects on radiative transfer. To estimate the true water leaving radiance from the TOA radiance it is necessary to remove the reflection at the water surface by sun- and sky glint and whitecaps. A good introduction to the underlying physics is given by Mobley et al., 2016.

Note that as the number of spectral bands and their resolution increases (e.g. from a few

multispectral bands to through to imaging spectrometry) it becomes increasingly feasible to use the satellite sensor spectral data itself to perform the required correctionsto estimate the atmospheric parameters from the image itself. Alternatively, by flying our proposed sensor(s) in tandem with atmospheric characterisation satellites, the required atmosphere parameterisation data can be obtained.

The steps that need to be considered to assess the BOA (water leaving radiance or reflectance at or just below water level) are as follows:

1. Select pixels that are in the water, not obscured by clouds, cloud shadows, smoke, fog, aircraft contrails etc., and not affected by reflectance of floating objects and emerging vegetation.

2. Identify pixels that are affected by sun/sky glint and whitecaps reflection and either discard them or correct for this additional reflectance source.

3. Correct the observed signal for gaseous absorption using assumed values or external data sources for O2, O3, and NO2 etc.

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4. Correct the observed signal for Rayleigh scattering using knowledge about topographical location, height (water bodies exist from -430 m to in excess of 5900 m altitude) and time. 5. Estimate the amount of water vapour and aerosol scattering per pixel (or per image) and

correct the signal for water vapour and aerosol absorption and scattering.

6. Correct for contamination of the pixel reflectance from nearby, high reflecting targets (adjacency effect).

7. (Optional) Couple the atmospheric correction to an in-water model to solve the RTE for the total water-atmosphere system and obtain optical closure.

There are several types of approaches to estimate the true water leaving radiance or reflectance from the compound signal measured at TOA. Overviews of such approaches have been published by e.g. (Goyens et al., 2013, Muller et al., 2015, Minu and Shetty, 2015, Emberton, 2016 etc.). All authors conclude that there is currently not a single suitable method for all situations. Situations that need further development include (very) turbid waters and conditions with strongly absorbing aerosols. Adjacency correction methods need to be addressed properly. A method to pre-select a suitable inland waters atmospheric correction based on optical water type classification was recently proposed by Eleveld et al., 2017. It is desirable, however, to have one generic method for

atmospheric correction over inland, coastal and coral reef waters.

Based on inquiries amongst participating scientists the GLaSS project (www.glass-project.eu) made a list of scientific and operational criteria that may help to select an appropriate atmospheric

correction scheme for inland waters. These include:

• Adaptable to a multitude of sensors (legacy missions, Sentinel-2, Sentinel-3, L8, future missions).

• Preferably open access, well documented, no other commercial software required, future maintenance assured.

• Wide range of AOT and atmospheric models. • With adjacency correction (possibility).

• Configurable for optical properties of atmosphere and water. • Configurable for ancillary data (e.g. O3, NO2), site elevation • Suitable physical range of the underlying radiative transfer model • Pixel wise retrievals of AOT and H2O vapour

Here we briefly discuss three approaches to atmospheric correction: 1. Methods inherited from ocean colour remote sensing:

These include methods based on more or less analytical solutions to the RTE (Gordon & Wang, 1994, Ruddick et al., 2000, etc., see Goyens et al., 2013). They start with assuming that there is no water leaving signal in the NIR and derive aerosol optical properties from that assumption. For turbid waters the zero reflectance in the NIR is not true, which lead to approaches deriving aerosol optical properties from SWIR bands where the water absorption is so high it overwhelms any backscattering by suspended matter (e.g. Vanhellemont and Ruddick, 2015, Moore and Lavender, 2011, Mazeran et al., (2011)). An alternative approach is to derive aerosol concentrations from nearby land pixels (Guanter et al., ,2010, Pons et al., 2014 and Xu et al., 2016).

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2. Methods that invert RT codes (LOWTRAN, MODTRAN, 5S, 6S):

These methods were often applied for atmospheric correction of airborne remote sensing over inland and coastal waters. A recent review was given by Minu and Shetty, 2015. Additional studies evaluating such approaches are e.g. Sterckx and Debruyn (2004), Montes and Gao (2004), Adler- Golden et al., (2005), Brando and Dekker (2003), Giardino et al., (2007), Guanter et al., (2010), Knaeps et al., 2012; Sterckx et al., 2015, Bagheri et al., 2004 and Peters et al., 2008. Although the advantage is that the radiative transport is well described by the standard code, one must pre-select an appropriate atmosphere and aerosol type which is subsequently kept constant over the image.

3. Methods that simultaneously retrieve atmospheric and water components:

Several spectral matching or neural network techniques (Doerffer and Schiller (2007), Schroeder et al., (2007), Heege et al., (2005), Steinmetz et al.,(2011), Kuchinke et al., (2009) and Xu et al., (2016)) which simultaneously retrieve atmospheric and water components have been developed. These algorithms can manage optically complex waters from inland to coastal. It should be noted that because the parameters of the atmosphere, the air-water interface and the water body are retrieved simultaneously an error in the coefficients of any parameter will impact the retrieval of all

parameters, whereby some effect may cancel each other out and some effects may exacerbate errors.

The use of hyperspectral data will reduce the ambiguity in the retrieval of the different parameters. Alternatively use can be made of other satellite sensors that are designed to measure these

atmospheric variables- of course there needs to be near simultaneous measurement by this suite of sensors. Extension of the wavelength range either into the ultraviolet or into the SWIR will improve the removal of atmospheric effects.