Phase functions of light scattering measured in waters of world ocean and lake Baykal

Mankovsky, V. I.; Haltrin, Vladimir I.

doi:10.1109/igarss.2002.1027252

Cited by 12 publications

(12 citation statements)

References 2 publications

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“…Recently, based on VSFs observations in the southern Baltic Sea, Freda (2012) [12] found that φp(140,λ) increases linearly with wavelength (r 2 >0.99). Using our measured VSFs as well as tabulated VSFs in the literature [17][18][19][20][21], we verify this relation; we compare bbp, Freda, bbp(λ) estimated using φp(140,λ) derived from this relation in Eq. (4), with bbp, integral, bbp(λ) directly determined using Eq.…”

Section: B Particulate Conversion Factor For B Bp (λ)supporting

confidence: 59%

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Accurate estimation of the backscattering coefficient by light scattering at two backward angles

Tan¹,

Oishi

Tanaka

et al. 2015

Appl. Opt.

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Backscattering coefficients are frequently estimated from light scattering at one backward angle multiplied by a conversion factor. We determined that the shapes of the volume scattering functions (VSFs), particularly for scattering angles larger than 170°, cause significant variations in the conversion factor at 120°. Our approach uses the ratio of scattering at 170° and at 120°, which is a good indicator of the shape differences of the VSFs for most oceanic waters and wavelengths in the visible range. The proposed method provides significant accuracy improvement in the determination of the backscattering coefficients with a prediction error of 3% of the mean.

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Section: B Particulate Conversion Factor For B Bp (λ)supporting

confidence: 59%

“…Quantified errors from the fixed-angle approach using νp [Rp(120,170)] and χp, mean(120) are provided in the third and fourth columns of Table 4. We evaluated 411 VSF datasets, including VSFs measured here (N=304) and VSFs from the literature (N=107) [17][18][19][20][21].…”

Section: Table 4 Summary Of Quantified Errors In the Fixed-angle Appmentioning

confidence: 99%

Accurate estimation of the backscattering coefficient by light scattering at two backward angles

Tan¹,

Oishi

Tanaka

et al. 2015

Appl. Opt.

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“…1). For example, B p values estimated from our measured VSFs vary over a factor of 30 from 0.0015 to 0.0543, which is much greater than the range of 0.0073-0.0194 estimated from Petzold's measurements and the range of 0.002-0.020 measured in Tonizzo et al [16], but comparable to the range of 0.0015-0.0454 reported in Mankovsky and Haltrin [34,35] over the oceans and lakes worldwide.…”

Section: Introductionsupporting

confidence: 54%

Re-examining the effect of particle phase functions on the remote-sensing reflectance

Xiong

Zhang

et al. 2017

Appl. Opt.

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Even though it is well known that both the magnitude and detailed angular shape of scattering (phase function, PF), particularly in the backward angles, affect the color of the ocean, the current remote-sensing reflectance (R) models typically account for the effect of its magnitude only through the backscattering coefficient (b). Using 116 volume scattering function (VSF) measurements previously collected in three coastal waters around the U.S. and in the water of the North Atlantic Ocean, we re-examined the effect of particle PF on R in four scenarios. In each scenario, the magnitude of particle backscattering (i.e., b) is known, but the knowledge on the angular shape of particle backscattering is assumed to increase from knowing nothing about the shape of particle PFs to partially knowing the particle backscattering ratio (B), the exact backscattering shape as defined by β˜(γ≥90°) (particle VSF normalized by the particle total scattering coefficient), and the exact backscattering shape as defined by the χ factor (particle VSF normalized by the particle backscattering coefficient). At sun zenith angle=30°, the nadir-viewed R would vary up to 65%, 35%, 20%, and 10%, respectively, as the constraints on the shape of particle backscattering become increasingly stringent from scenarios 1 to 4. In all four scenarios, the R variations increase with both viewing and sun angles and are most prominent in the direction opposite the sun. Our results show a greater impact of the measured particle PFs on R than previously found, mainly because our VSF data show a much greater variability in B, β˜(γ≥90°), and χ than previously known. Among the uncertainties in R due to the particle PFs, about 97% can be explained by χ, 90% by β˜(γ≥90°), and 27% by B. The results indicate that the uncertainty in ocean color remote sensing can be significantly constrained by accounting for χ of the VSFs.

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“…For example, the averaged ratio of R − R 0 to R exceeds 0.05 (5%) when c · h ¼ 10 −0.2 ≅ 0.63 and r b ¼ 0.4, as indicated in the figure by the symbol "×." Here, a c · h value of 0.63 corresponds to an h value of 2.1 m when c ¼ 0.3, and both of these values are not too small to be common: c < 0.3 has been observed in various locations in oceans and the Mediterranean for green wavelengths 19,23 and in a coral reef even at 660 nm. 29 An r b value of 0.4 is not a large value for carbonate sand in coral reefs: the average r b of 670 measurements by Hochberg 24 falls within 0.4 to 0.6 at wavelengths of 475 to 700 nm.…”

Section: Accuracy Assessmentmentioning

confidence: 99%

“…The c · h range handled in this paper corresponds to 0.05 to 19.91 m when c ¼ 0.2 (a possible value for clear seawater at blue and green wavelengths). 18,19,23 We set r b to cover a wide range of 0.1 to 0.6 with a small interval of 0.05. An r b value of 0.6 is possible for carbonate sand at green and red wavelengths.…”

Section: Radiative Transfer Simulationmentioning

confidence: 99%

Validation of shallow-water reflectance model for remote sensing of water depth and bottom type by radiative transfer simulation

Kanno

Tanaka

Sekine

2013

J. Appl. Remote Sens

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Abstract. Lyzenga proposed a shallow-water reflectance model that describes the exponential relationship between the remote-sensing reflectance (R) and water depth [Appl. Opt. 17, 379383 (1978)]. The model has been widely used in remote sensing of water depth to estimate the depth from R, and in remote sensing of bottom type to remove the effect of depth from R. Although it was derived from radiative transfer theory ignoring internal reflection at the water surface, no study has quantitatively validated it following the theory. In this study, we examine its accuracy under various conditions using Monte Carlo radiative transfer simulations. Although internal reflection contributed significantly to R in some cases, the model, if fitted to (calibrated with) data covering the entire target depth range, described the relationship between R and depth reasonably accurately (R 2 > 0.9935). This was because the internally reflected component of R, as well as the other component, decreases exponentially with depth. However, because the sum of two exponentially decreasing functions is not strictly exponential, the model does not accurately estimate the depth using R when the calibration data did not cover the entire depth range of interest: the model significantly underestimated the depth when used for extrapolation.

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Phase functions of light scattering measured in waters of world ocean and lake Baykal

Abstract: -A set of twenty previously unpublished phase functions of light scattering measured in situ in waters of oceans, seas and lake Baykal is presented in the tabular form. In 18 cases these measurements were accompanied by the independent measurements of beam attenuation coefficient.

Cited by 12 publications

References 2 publications

Accurate estimation of the backscattering coefficient by light scattering at two backward angles

Accurate estimation of the backscattering coefficient by light scattering at two backward angles

Re-examining the effect of particle phase functions on the remote-sensing reflectance

Validation of shallow-water reflectance model for remote sensing of water depth and bottom type by radiative transfer simulation

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