A comparative assessment on the use of SAR and high-resolution optical images in ocean dynamics studies

Gagliardini, Domingo A.; Colon, Pablo Clemente

doi:10.1080/01431160310001592166

Cited by 7 publications

(4 citation statements)

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“…Furthermore, the sun's glint can overshadow the upwelled water-leaving radiance during elevated solar angles. As Gagliardini et al [74] noted, this leads to noise in the image information. Overstreet and Legleiter [75] further demonstrated that sun glint might induce over-corrections in shallow areas of water in the imagery, producing unreliable data.…”

Section: Class Influence On the Resultsmentioning

confidence: 99%

U-Net Performance for Beach Wrack Segmentation: Effects of UAV Camera Bands, Height Measurements, and Spectral Indices

Tiškus,

Bučas,

Gintauskas

et al. 2023

Drones

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This study delves into the application of the U-Net convolutional neural network (CNN) model for beach wrack (BW) segmentation and monitoring in coastal environments using multispectral imagery. Through the utilization of different input configurations, namely, “RGB”, “RGB and height”, “5 bands”, “5 bands and height”, and “Band ratio indices”, this research provides insights into the optimal dataset combination for the U-Net model. The results indicate promising performance with the “RGB” combination, achieving a moderate Intersection over Union (IoU) of 0.42 for BW and an overall accuracy of IoU = 0.59. However, challenges arise in the segmentation of potential BW, primarily attributed to the dynamics of light in aquatic environments. Factors such as sun glint, wave patterns, and turbidity also influenced model accuracy. Contrary to the hypothesis, integrating all spectral bands did not enhance the model’s efficacy, and adding height data acquired from UAVs decreased model precision in both RGB and multispectral scenarios. This study reaffirms the potential of U-Net CNNs for BW detection, emphasizing the suitability of the suggested method for deployment in diverse beach geomorphology, requiring no high-end computing resources, and thereby facilitating more accessible applications in coastal monitoring and management.

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Section: Class Influence On the Resultsmentioning

confidence: 99%

U-Net Performance for Beach Wrack Segmentation: Effects of UAV Camera Bands, Height Measurements, and Spectral Indices

Tiškus,

Bučas,

Gintauskas

et al. 2023

Drones

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show abstract

“…[3] The Sun's direct reflection from the ocean surface, often referred to as Sun glitter or Sun glint, is also related to the sea surface roughness, and the radiation intensity of the reflection can be explained by the quasi-specular scattering theory [Cox and Munk, 1954;Gordon, 1997;Munk, 2009]. Variations in the sea surface roughness due to submarine topography can result in modulation of the radiance intensity in optical imageries and, as a result, submarine topographic features are frequently observed in optical satellite imageries since the launch of SKYLAB [Hennings et al, 1988[Hennings et al, , 1994Gagliardini and Colón, 2004;Matthews et al, 2008].…”

Section: Introductionmentioning

confidence: 99%

“…Variations in the sea surface roughness due to submarine topography can result in modulation of the radiance intensity in optical imageries and, as a result, submarine topographic features are frequently observed in optical satellite imageries since the launch of SKYLAB [Hennings et al, 1988[Hennings et al, , 1994Gagliardini and Colón, 2004;Matthews et al, 2008].…”

Section: Introductionmentioning

confidence: 99%

“…[4] Comparative studies [Hennings et al, 1988[Hennings et al, , 1994Gagliardini and Colón, 2004] between SAR and optical imageries show that each type of sensor has its own advantages and limitations when used to observe sea bottom features according to the way in which each detects sea surface roughness. Optical sensors are limited by the needs for cloud-free conditions, daylight, high solar azimuth and zenith angle months (e.g., from April to September in the Northern Hemisphere), while SAR sensors are capable of observing the sea surface under all-weather conditions throughout the year.…”

Section: Introductionmentioning

confidence: 99%

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Sun glitter imaging of submarine sand waves on the Taiwan Banks: Determination of the relaxation rate of short waves

Shao¹,

Li²,

Li³

2011

J. Geophys. Res.

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[1] Above sand waves on the seafloor, surface short waves, which are responsible for the radiance distribution in remote sensing imagery, are modulated gradually by the submarine topography. The relaxation rate m r characterizes the rate at which the short waves reach their saturation range after being disturbed. It is a key parameter in the weak hydrodynamic interaction theory and is also a most important parameter in the imaging mechanism used for mapping submarine bottom topography. In this study, a robust expression containing intensity and phase (advection effect) modulations of the perturbed action spectrum of short waves was deduced, by using the first-order weak hydrodynamic interaction theory. On the basis of the phase modulation, a method was developed to determine the relaxation rate in the Sun glitter imaging mechanism. The relaxation rates were estimated using in situ data measured on a cruise over the sand waves of the Taiwan Banks, a sea area between the East China Sea and the South China Sea, on 28-29 August 2006. Results showed that, under a wind speed of 5.0 m s −1 , the relaxation rate of short waves was about 0.055 s −1 in response to current variations and about 0.025 s −1 equivalently in response to sea bottom topographic variations. The former value could be applied to interpret the amplitude of submarine topography by using satellite imagery, while the latter one (equivalent relaxation rate m′ r ) could help to more accurately calibrate the spatial position of the retrieved sea bottom topography.

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A Comparison of Bathymetric Signatures Observed on ERS SAR and LANDSAT TM Images Over the Timor Sea

Thankappan

Smith

2009

Lecture Notes in Geoinformation and Cartography

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A comparative assessment on the use of SAR and high-resolution optical images in ocean dynamics studies

Cited by 7 publications

References 1 publication

U-Net Performance for Beach Wrack Segmentation: Effects of UAV Camera Bands, Height Measurements, and Spectral Indices

U-Net Performance for Beach Wrack Segmentation: Effects of UAV Camera Bands, Height Measurements, and Spectral Indices

Sun glitter imaging of submarine sand waves on the Taiwan Banks: Determination of the relaxation rate of short waves

A Comparison of Bathymetric Signatures Observed on ERS SAR and LANDSAT TM Images Over the Timor Sea

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