Remote measurement of water color

Mccluney, W. R.

doi:10.1016/0034-4257(76)90032-8

Cited by 15 publications

(4 citation statements)

References 39 publications

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“…A tank 90 cm deep and 366 cm in diameter was enclosed in a black plastic liner to minimize extraneous reflectance (McCluney, 1976;Manam, 1990, 1991;Han and Rundquist, 1994). The depth of the water column was 80 cm.…”

Section: Design Setup For Reflectance Measurementmentioning

confidence: 99%

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS¹

Lodhi¹,

Rundquist²,

Han³

et al. 1997

J American Water Resour Assoc

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The potential for detecting the concentration and type of soils suspended in surface water through remote sensing techniques was investigated by studying the spectral reflectance of two types of soils in suspension. In a large tank filled with 7510 liters of water, 20 levels of suspended sediment (soil) concentration (SSC), ranging from 50 to 1000 mg/l were prepared. A high resolution spectroradiometer was used to measure the reflectance at each SSC level. The reflectance spectra of two contrasting soils were distinct in the visible and near infrared (NIR) portions of the electromagnetic spectrum. The wavelength range between 580–690 nm (visible) was found to be optimal for indicating the type of soil, whereas, the wavelength range between 714–880 (NIR) was found to be appropriate for estimating the concentration of sediment suspended in surface waters.

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Section: Design Setup For Reflectance Measurementmentioning

confidence: 99%

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS¹

Lodhi¹,

Rundquist²,

Han³

et al. 1997

J American Water Resour Assoc

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“…The accuracy with which the chlorophyll-like pigment concentrations can be determined from the CZCS data, therefore, depends largely upon the accuracy with which the atmospheric variables are known. Many authors (Curran 1972, McCluney 1976, Gordon 1978,· Mehl and Melchior 1979, Gordon 1981 have discussed various types of errors involved in the determination of pigment concentrations by remote-sensing techniques. Some of the requirements for better accuracy in the atmospheric correction method have been summarized by Serensen (1979 a).…”

Section: Sources Of Errorsmentioning

confidence: 99%

Comparison between CZCS data from 10 July 1979 and simultaneous in situ measurements for south-eastern Scottish waters

Singh¹,

Cracknell²,

Charlton

1983

International Journal of Remote Sensing

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This paper presents an analysis of coastal zone colour scanner (CZCS) data for a date for which simultaneous in situ measurements exist.Using CZCS data of 10 July 1979 for the vicinity of Dundee, the inflight slope and intercept for all spectral bands were calculated. Comparison of these results with the pre-flight values show that the deviations of the inflight slopes from the pre-flight slopes for the visible bands are within II per cent, whereas the deviations in the intercepts are found to be rather larger. The contribution to the satellite-recorded radiance from the atmospheric interplay was removed using Sturm's atmospheric correction method which incorporates the iteration procedure described by Smith and Wilson.Many algorithms have been used for comparing the upwelling radiance with the in situ chlorophyll-like pigment concentrations. Although, some of the algorithms gave good correlation coefficients, the constants in the algorithms used turn out to be quite different from the values which have been obtained by other investigators. We have also computed the sea-surface temperatures from the infrared band data and the inflight calibration constants, but no atmospheric correction was applied to the infrared band data.We have used NASA's.chlorophyll algorithms (with given parameters), one for low chlorophyll concentrations and the other for high chlorophyll concentrations for calculating the chlorophyll concentrations for those pixels within which the in situ measurements were made. The low-chlorophyll algorithm gives the chlorophyll concentrations which are smaller by a factor of about 4 than the in situ data. The results obtained from the high-chlorophyll concentration algorithm are within a factor of about 2 of the measured values.The error in the determination of chlorophyll-like pigment concentrations from the CZCS data due to factors hitherto ignored in practice by other workers is shown to be as large as the error due to the inherent signal-to-noise ratio. The factors considered here are (a) the wavelength dependence of the refractive index of seawater, (b) the variation in the temperature and salinity of seawater and (c) the choice of different values of the refractive index of seawater by individual investigators. The results are presented in such a manner that an investigator having no in situ data can estimate the errors due to these factors in the chlorophyll-like pigment concentrations computed from the CZCS data alone.We have also investigated the effect of the revised values of the solar irradiances on the chlorophyll-like pigment algorithm and we recommend that all those algorithms which are based on the original values of the solar irradiances must be revised using the new recommended values of the solar irradiances. If this is not done then the error in the derived product is shown to be about 169 per cent. Downloaded by [Massachusetts Institute of Technology] at 10:05 26 November 2014 756 S. M. Singh et al.

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“…Although it is relatively easy to detect differences within and among lakes, it is more difficult to attach physical, 963 chemical, or biological significance to the color, particularly when quantitative estimates are desired (Blackwell and Boland, 1979). The difficulty is compounded in waters having more than one class of particulates present, which is normally the case in natural water (McCluney, 1976). Wezernak and Polcyn (1972) examined the question of making eutrophication assessments from the current remote sensing technology.…”

Section: Scherz Et Almentioning

confidence: 99%

CURRENT USE AND TECHNOLOGY OF LANDSAT MSS DATA FOR LAKE TROPHIC CLASSIFICATION¹

Witzig

Whitehurst

1981

J American Water Resour Assoc

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The trophic characterization of lakes has been intermittently monitored in recent years with data generated from satellite and aircraft spectral scanners. Each of these methods used “ground truth” (lake sampling data) to establish a correlation between scanner‐recorded radiance values and a trophic index for each lake (or portion of a lake). The approaches varied in their processing of the digital imagery, as well as in the development of trophic indices. Currently, several states employ varying spectral imagery techniques to develop lake classifications to satisfy the requirements of Section 314 of Federal Water Pollution Control Act. These variations have created a need for developing a uniform, tested approach for use by states and EPA for the description of lake trophic state from multispectral imagery. The current state and the use of multispectral data and technology to determine lake trophic indices is assessed in this paper.

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Remote measurement of water color

Cited by 15 publications

References 39 publications

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS¹

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS¹

Comparison between CZCS data from 10 July 1979 and simultaneous in situ measurements for south-eastern Scottish waters

CURRENT USE AND TECHNOLOGY OF LANDSAT MSS DATA FOR LAKE TROPHIC CLASSIFICATION¹

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Remote measurement of water color

Cited by 15 publications

References 39 publications

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS1

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS1

Comparison between CZCS data from 10 July 1979 and simultaneous in situ measurements for south-eastern Scottish waters

CURRENT USE AND TECHNOLOGY OF LANDSAT MSS DATA FOR LAKE TROPHIC CLASSIFICATION1

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THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS¹

THE POTENTIAL FOR REMOTE SENSING OF LOESS SOILS SUSPENDED IN SURFACE WATERS¹

CURRENT USE AND TECHNOLOGY OF LANDSAT MSS DATA FOR LAKE TROPHIC CLASSIFICATION¹