# Automatic Sun Glint Removal of Multispectral High-Resolution Worldview-2 Imagery for Retrieving Coastal Shallow Water Parameters

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Methodology

- (i)
- A radiometric calibration and optimal atmospheric correction model.
- (ii)
- A novel automatic algorithm for sun glint removal based on physical modeling.
- (iii)
- A multichannel physics-based algorithm which integrates the new deglinting technique and the Radiative Transfer Equations for monitoring and mapping coastal shallow water parameters: Inherent Optical Properties, water depth and bottom reflectance.

**Figure 1.**Schematic procedure of the proposed multispectral high resolution WorldView-2 processing chain for shallow coastal waters applications.

#### 2.1. WorldView-2 Multispectral Imagery and Study Area

**Figure 2.**(

**a**) Location of study area (The Canary Islands); (

**b**,

**c**) WV-2 images of two Canary Islands singular littoral zones: (

**b**) Maspalomas (Gran Canaria Island, 11 August 2013) area; and (

**c**) Corralejo-Lobo Island (Fuerteventura Island, 28 October 2010) area.

#### 2.2. Atmospheric Correction Algorithm

#### 2.3. Sun Glint Multispectral Data Correction Algorithm

_{i}) of NIR brightness against the visible band brightness, as follows,

^{2}= 0.9573, obtaining a slope parameter b = 0.9373.

R7 | R8 | R^{2} | a | b | min (ρ_{TOC} (NIR)) | |
---|---|---|---|---|---|---|

R1 | X | 0.8513 | 0.04074 | 0.7854 | 0.0064 | |

R2 | X | 0.9561 | 0.03918 | 0.8943 | 0.0082 | |

R3 | X | 0.9373 | 0.01605 | 0.9673 | 0.0082 | |

R4 | X | 0.8836 | 0.01434 | 0.9848 | 0.0064 | |

R5 | X | 0.9582 | 0.006162 | 1.003 | 0.0082 | |

R6 | X | 0.7946 | 0.004212 | 1.007 | 0.0064 |

_{i}parameter corresponds to the quite clear ocean water reflectance (being a greatly reduced reflectance), when the glint contribution is null. The other important fact that we can observe is how the b

_{i}parameter tends to 1 when the bands move towards the NIR band wavelength.

_{i}, which is calculated from an empirical way in the traditional algorithm.

_{i}. Therefore, the simplified model is:

- ▪
- A-route is the down directed sun beam.
- ▪
- B-route is the scattering of the atmosphere to the water surface and then reflected to the satellite (sky-glint).
- ▪
- C-route is the water-leaving reflectance transmitted through the atmosphere and the air-water surface.
- ▪
- D-route is the specular reflection of the water surface (sun glint).
- ▪
- E-route is the single or multiple backscattering of the atmosphere (Rayleigh and aerosol).

**Figure 4.**Simplified schematic diagram showing routes by which light reaches a remote sensing detector.

^{2}pixel contains some facets with different incident angles obtained in small time windows, we can use the statistical approach, used in low resolution images, to present the problem [13,16],

_{λ}is the irradiance incident on the surface, ${\rho}_{\lambda}^{Fresnel}\left(\omega \right)$ is the Fresnel reflectance with respect the incident angle (ω), $P\left({\theta}_{v},{\theta}_{s},{\phi}_{s},{\phi}_{v}\right)$ is the provability of specular surface with respect the solar and satellite zenith angles (${\theta}_{s},{\theta}_{v}$) and the solar and satellite azimuth angles (${\phi}_{s},{\phi}_{v}$), β is the slope inclination angle relative to the flat surface.

R1 | R2 | R3 | R4 | R5 | R6 | R7 | R8 | |
---|---|---|---|---|---|---|---|---|

${\mathit{E}}_{\mathit{b}\mathit{a}\mathit{n}\mathit{d}}^{\mathit{N}\mathit{D}\mathit{i}\mathit{r}}$ | 0.214 | 0.158 | 0.114 | 0.091 | 0.077 | 0.067 | 0.058 | 0.052 |

${\mathit{E}}_{\mathit{b}\mathit{a}\mathit{n}\mathit{d}}^{\mathit{N}\mathit{D}\mathit{i}\mathit{f}}$ | 0.786 | 0.842 | 0.886 | 0.909 | 0.923 | 0.933 | 0.942 | 0.948 |

$\frac{{\mathit{E}}_{\mathit{\lambda}}^{\mathit{N}\mathit{D}\mathit{i}\mathit{r}}}{{\mathit{E}}_{\mathit{N}\mathit{I}\mathit{R}}^{\mathit{N}\mathit{D}\mathit{i}\mathit{r}}}$ | 0.829 | 0.893 | 0.941 | 0.958 | 0.979 | 0.984 | - | - |

_{i}, obtained through linear fitting, versus the ratio of 6S direct irradiance parameters.

**Figure 6.**Slope b

_{i}, obtained by linear fitting (

**blue**); and optical-band/NIR direct irradiance ratio (

**red**).

_{i}, where such areas must be deep and without turbidity. This is not always possible in shallow coastal environments and in inland waters, allowing, as well, to obtain a fully automatic deglinting algorithm,

#### 2.4. Deglinting Algorithm Integrated into the Radiative Transfer Modeling (RTM)

_{d}) and the relationship between the seafloor albedo, its depth and the water Inherent Optical Properties (IOPs), since they are a function of water quality and the chlorophyll-a, turbidity, and CDOM concentrations. In consequence, the RTE allows us to model the reflectivity and it can be expressed by [1,4,18,19],

_{d}is the diffuse attenuation coefficient; and z is the depth [19,20,21,22].

## 3. Results and Discussion

_{d}) is an important water property related to light penetration and availability in aquatic systems.

^{3}) can be observed. Figure 8b represents the Chl-a concentration using the classic deglinting + RTE algorithm. On the other hand, the Chl-a concentration using the new automatic deglinting algorithm integrated in the RTE model is shown in Figure 8c. Comparing both results with in situ data, a more accurate remote measurement with the new approach can be observed. It can be seen in Figure 8b as the high turbidity of lake water increases the reflectance in the NIR band to the point of introducing significant errors in the estimation after subtracting the NIR reflectance in the classic sun glint removal algorithm.

_{d}(490) coefficient map, using the new deglinting algorithm integrated in the RTE model, of Corralejo-Lobo Island (Fuerteventura Island) is shown in Figure 9a. We can observe in the Figure 9a more details in the information of the water quality and the local-scale structures. Modeling the non-negligible reflectivity in the NIR band improves the sensitivity to detect the water quality in shallow waters. A more accurate determination of water quality allows detecting local structures which determine the direction of the currents and the functioning of the coastal dynamics [25]. On the other hand, results of seafloor albedo are presented in Figure 9b, after using the new deglinting algorithm integrated in the RTE model, for the selected Corralejo-Lobo Island littoral zones. The existence of the NIR reflectivity, from the seabed albedo, which is subtracted in the other bands in the classic deglinting algorithm, results in a loss of quality in the retrieving of the seabed albedo. In Figure 9b we can appreciate how after modeling the NIR reflectance band, this non-negligible contribution of reflectance, can be removed from the correction to yield higher albedos in the very low depths.

**Figure 8.**(

**a**) In situ Chl-a samples in Maspalomas inner lake; (

**b**) Chl-a concentration map by using classical + RTE deglinting algorithm; (

**c**) Chl-a concentration map by using developed deglinting algorithm.

**Figure 9.**Corralejo and the Lobo Island (Fuerteventura Island), biosphere reserve and natural protected area: (

**a**) k

_{d}(490) coefficient map; and (

**b**) color composite of the seafloor albedo obtained using the new deglinting integrated in the RTE inversion algorithm.

**Figure 10.**Maspalomas coastal shallow water bathymetry: (

**a**) Sonar bathymetry; and (

**b**) bathymetry map by using the new deglinting algorithm integrated in the RTE model.

_{i}) used in the elimination of the sun glint through the NIR channel. To obtain this expression, the assumption that the refractive index is independent of the wavelength has been considered. Such assumption is systematically used in all sun glint correction algorithms on high resolution images. Anyhow, the minimum refractive index variation of the water with respect to the wavelength of the optical bands allows this approach to introduce very small errors. The proposed method, by eliminating the empirical calculation of the parameter (b

_{i}) using a linear fitting of the reflectivity bands, allows us to remove errors associated with the line regression like outliers generated by the foam, errors in the image resampling or the lack of time synchronization in the image bands. Similarly, the absence of deep water areas without turbidity in the image makes empirical characterization methods ineffective. Finally, integrating sun glint correction algorithm in the radiative transfer modeling is an attempt to solve the main assumption that the reflectivity of water in the NIR channel is negligible. This assumption creates significant errors under very shallow water and high turbidity conditions, so modeling the water reflectivity in the NIR channel allows us mitigate these errors.

## 4. Conclusions

_{i}relating the glint of the NIR with each of the optical bands analytically. This has permitted us to create a fully automatic algorithm which can be used in scenarios where classic empirical algorithms could not get the b

_{i}parameter, as in very shallow waters or inland waters.

## Acknowledgments

## Author Contributions

## Conflicts of Interest

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**MDPI and ACS Style**

Martin, J.; Eugenio, F.; Marcello, J.; Medina, A. Automatic Sun Glint Removal of Multispectral High-Resolution Worldview-2 Imagery for Retrieving Coastal Shallow Water Parameters. *Remote Sens.* **2016**, *8*, 37.
https://doi.org/10.3390/rs8010037

**AMA Style**

Martin J, Eugenio F, Marcello J, Medina A. Automatic Sun Glint Removal of Multispectral High-Resolution Worldview-2 Imagery for Retrieving Coastal Shallow Water Parameters. *Remote Sensing*. 2016; 8(1):37.
https://doi.org/10.3390/rs8010037

**Chicago/Turabian Style**

Martin, Javier, Francisco Eugenio, Javier Marcello, and Anabella Medina. 2016. "Automatic Sun Glint Removal of Multispectral High-Resolution Worldview-2 Imagery for Retrieving Coastal Shallow Water Parameters" *Remote Sensing* 8, no. 1: 37.
https://doi.org/10.3390/rs8010037