Retrieval of Higher Order Ocean Spectral Information From Sunglint

Cureton, Geoff

doi:10.1109/tgrs.2014.2317477

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…This behavior agrees with the results presented by Álvarez-Borrego [12] and Cureton [8] for the Gaussian case. The results derived in this letter involve the results from a first to a third approximation according to Longuet-Higgins [5].…”

Section: Discussionsupporting

confidence: 92%

“…Therefore, when the camera is at a larger height, the sensor will receive more light reflections from smaller incidence angles. Thus, we can say that the results presented by Álvarez-Borrego [12], Cureton [8], and Álvarez-Borrego and Martín-Atienza [1] are correct for the Gaussian case. Figs.…”

Section: Relationships Among the Variances Of The Intensities Inmentioning

confidence: 63%

“…p(M i ) is the probability density function, where a non-Gaussian function is considered in one dimension [8], i.e.,…”

Section: Relationships Among the Variances Of The Intensities Inmentioning

confidence: 99%

“…where τ is the lag, and p(M 1i , M 2i ) is defined by [8], which is a generalization to the Gram Charlier series presented by Cox and Munk [2], i.e., In order to avoid memory computer problems, the 16 384 data points profile was divided into consecutive intervals. The value of θ d varies from point to point in the profile.…”

Section: Relationships Among the Variances Of The Intensities Inmentioning

confidence: 99%

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Some Statistical Properties of Surface Slopes via Remote Sensing Using Variable Reflection Angle Considering a Non-Gaussian Probability Density Function

Álvarez-Borrego

Martin-Atienza

2013

IEEE Geosci. Remote Sensing Lett.

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Relationships to obtain information concerning some statistical properties of surface slope from statistical properties of the image intensity in remotely sensed images, considering a variable detector line-of-sight angle, are shown. The brightness distribution in sunlight reflected from the ruffled sea surface is related to the joint probability distribution of the two components of surface slope. A 1-D section through the brightness distribution provides values of the joint distribution along a line through the joint distribution. Considering the assumption that all the ocean waves are moving along a single direction and that the observer and the sun are both in the vertical plane containing this direction, a new expression between the variance of the intensity in the image and the variance of the surface slopes is derived considering a non-Gaussian statistics where the skewness and kurtosis moments are taken into account. The relation between correlation functions of the intensities in the image and surface slopes is numerically analyzed; in the non-Gaussian statistics, the skewness moment was considered only. The 1-D case is considered, and the results are graphically presented.

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Section: Discussionsupporting

confidence: 92%

Section: Relationships Among the Variances Of The Intensities Inmentioning

confidence: 63%

“…p(M i ) is the probability density function, where a non-Gaussian function is considered in one dimension [8], i.e.,…”

Section: Relationships Among the Variances Of The Intensities Inmentioning

confidence: 99%

Section: Relationships Among the Variances Of The Intensities Inmentioning

confidence: 99%

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Some Statistical Properties of Surface Slopes via Remote Sensing Using Variable Reflection Angle Considering a Non-Gaussian Probability Density Function

Álvarez-Borrego

Martin-Atienza

2013

IEEE Geosci. Remote Sensing Lett.

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“…In ocean science, the waves in surf zone (high-frequency component) are difficult to be modelled purely using satellite imagery information. Although sun glint data can be used for extracting the sea surface geometry and dynamics (Cureton, 2015), most of the related applications have, so far, neglected the ocean wave influences and assumed that water surface is planar. Ideally, a calmer sea condition is preferable to minimize the error caused by waves.…”

Section: Other Errorsmentioning

confidence: 99%

Shallow water bathymetry from WorldView-2 stereo imagery using two-media photogrammetry

Cao

Fang

Jiang

et al. 2019

European Journal of Remote Sensing

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Two-media photogrammetry appears to be a useful technology for mapping shallow water depth. The objective of this paper is to explore the feasibility of shallow water bathymetry using satellite two-media photogrammetry. This paper presents a two-media photogrammetry technique for WorldView-2 stereo multispectral imagery. In this method, near-infrared band is used for sun glint elimination. A combination of Scale Invariant Feature Transform and Semi-Global Matching algorithm is adopted for dense stereo matching. Rational Function Model is applied for raw Digital Elevation Model generation and the water surface elevation is determined by interpolating water edge elevation. Finally, the approximate refraction correction model is adopted in the water region to correct the vertical coordinate offsets. Our experimental results of Ganquan Island and Zhaoshu Island show that a reasonable depth estimate with relative error less than 17% and 14% can be obtained for the water depth range between 5 and 20 m, and the root-mean-square error are 2.09 m and 1.76 m, respectively. However, less accurate estimate is found for the very shallow water depth range between 0 and 5 m. The overall accuracy of satellite two-media photogrammetry is at the same level with the traditional multispectral-based model for bottom depth retrieval. ARTICLE HISTORY

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