Determinations of suspended sediment concentrations from multiple day landsat and AVHRR data

Lyon, J. G.; Bedford, Keith W.; Yen, Chieh-Cheng J.; Lee, Deborah H.; Mark, David J.

doi:10.1016/0034-4257(88)90044-2

Cited by 27 publications

(10 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Satellite remote sensing has also been used to estimate the concentrations of surface TSS. Lyon et al (1988) determined that Landsat and Advanced Very High Resolution Radiometer (AVHRR) imagery could be used to categorize surface sediment concentration trends that corresponded with hydrodynamic and water quality model simulations for Sandusky Bay, Lake Erie. More recently, Miller and McKee (2004) demonstrated the application of MODIS (Terra) 250 m data to quantify TSS using a linear regression model relationship established between MODIS band-1 (620–670 nm) and in situ measurements of concentrations of inorganic-dominated TSS or Fixed Suspended Solids (FSS) in the coastal northern Gulf of Mexico ( R 2 =0.89, n =52).…”

Section: Introductionmentioning

confidence: 99%

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary, USA

Lunetta

Knight

Paerl

et al. 2009

International Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

The monitoring of water colour parameters can provide an important diagnostic tool for the assessment of aquatic ecosystem condition. Remote sensing has long been used to effectively monitor chlorophyll concentrations in open ocean systems; however, operational monitoring in coastal and estuarine areas has been limited because of the inherent complexities of coastal systems, and the coarse spectral and spatial resolutions of available satellite systems. Data were collected using the National Aeronautics and Space Administration (NASA) Advanced Visible-Infrared Imaging Spectrometer (AVIRIS) flown at an altitude of approximately 20000 m to provide hyperspectral imagery and simulate both MEdium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectrometer (MODIS) data. AVIRIS data were atmospherically corrected using a radiative transfer modelling approach and analysed using band ratio and linear regression models. Regression analysis was performed with simultaneous field measurements data in the Neuse River Estuary (NRE) and Pamlico Sound on 15 May 2002. Chlorophyll a (Chl a) concentrations were optimally estimated using AVIRIS bands (9.5 nm) centred at 673.6 and 692.7 nm, resulting in a coefficient of determination (R2) of 0.98. Concentrations of Chromophoric Dissolved Organic Matter (CDOM), Total Suspended Solids (TSS) and Fixed Suspended Solids (FSS) were also estimated, resulting in coefficients of determination of R2=0.90, 0.59 and 0.64, respectively. Ratios of AVIRIS bands centred at or near those corresponding to the MERIS and MODIS sensors indicated that relatively good satellite-based estimates could potentially be derived for water colour constituents at a spatial resolution of 300 and 500 m, respectively.

show abstract

Section: Introductionmentioning

confidence: 99%

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary, USA

Lunetta

Knight

Paerl

et al. 2009

International Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Many investigators have addressed the issue of estimating suspended sediments with remote sensing (Alfoldi and Munday, 1978;Amos and Alfoldi, 1979;Amos and Toplis, 1985;Curran et al, 1987;Curran and Novo, 1988;Aranuvachapun and Walling, 1988;Lyon et al, 1988;Doerffer et al, 1989;Ritchie et al, 1990;Schiebe et al, 1992;Goodin et al, 1993;Mayo et al, 1993;Han and Rundquist, 1994 suspended sediment concentration in surface waters. However, few addressed the issue of reflectivity differences in between different types of soil materials.…”

Section: Introductionmentioning

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

View full text Add to dashboard Cite

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.

show abstract

“…This difference is probably due to the higher surface suspended sediment concentrations in Moon Lake (average 110 mg/i) and Lake Chicot (average 183 mg/i). Previous laboratory (Chen et al, 1991;Whitlock et al, 1981), in situ (Ritchie et al, 1976), and Landsat MSS (Lyons et al, 1988;Ritchie and Cooper, 1988;Schiebe et al, 1988;Topliss et al, 1990) studies show that reflectance in wavelengths between 0.6 and 0.8 p.m related best to surface suspended sediment concentrations and that reflectance from surface suspended sediments was related to wavelength and concentration. As wavelength increased from 0.4 to 1.0 p.m, the concentration of surface suspended sediments needed to reach maximum reflectance increased.…”

Section: Surface Suspended Sediment Concentrations Inmentioning

confidence: 91%

“…Conservation plans and actions could be directed toward those watersheds with the greatest erosion problems. Studies have shown good relationships between changes in surface suspended sediments and spectral data (Carpenter and Carpenter, 1983;Chen et al, 1991;Harrington et al, 1989;Lathrop and Lillesand, 1986;Lindell et al, 1986;Lyons et al, 1988;Ritchie et al, 1986Ritchie et al, , 1989Ritchie and Cooper, 1988;Schiebe et al, 1988;Verdin, 1985). These studies were site specific and used field data to relate surface suspended sediment concentrations to spectral measurements.…”

Section: Introductionmentioning

confidence: 97%

AN ALGORITHM FOR ESTIMATING SURFACE SUSPENDED SEDIMENT CONCENTRATIONS WITH LANDSAT MSS DIGITAL DATA¹

Ritchie¹,

Cooper

1991

J American Water Resour Assoc

View full text Add to dashboard Cite

Algorithms for Landsat MSS digital data are needed to reduce the necessity of calibrating each Landsat scene if these data are to be useful in monitoring programs for surface suspended sediments. In this study digital data were extracted from 16Landsat Multispectral Scanner (MSS) scenes collected between March 1987 and August 1988 over Enid Reservoir in North Central Mississippi. These data were converted to radiance and reflectance data for comparison with field measurements of surface suspended sediment concentrations. Concentrations ranged from 2 to 168 mg/i during the study with only four greater than 100 mg/i. Linear and polynomial regression analyses were used to relate the surface suspended sediment concentrations with radiance and reflectance.Reflectance in MSS band 2 (0.6 to 0.7 tm) and MSS band 3 (0.7 to 0.8 tm) were best related to the surface suspended sediment concentrations with coefficients of determination accounting for 71 percent and 68 percent of the variation in the data, respectively.Regressions with radiance data accounted for 36 percent (band 2) or less of the variation. Logarithmic transformations of either reflectance or sediment concentrations increase the coefficients of determination for MSS band 2 reflectance data to 81 percent. Regressions between the ratio of MSS band 1 to MSS band 2 reflectances and concentrations also accounted for 80 percent of the variation. An equation Loge SS (mg/i) = 9.21R12 + 2.71R/2 + 8.45, where S is surface suspended sediment concentrations and R is the ratio of MSS band 1 to MSS band 2 reflectances, provided the best fit to the data with a coefficient of determination of 0.82. This equation is essentially the same as an algorithm proposed by Topliss et at. (1990), for estimating surface suspended sediment concentrations in Canadian coastal waters. These equations for Enid Reservoir and Canadian waters suggest that it may be possible to develop an algorithm for widespread use for estimating surface suspended sediments.

show abstract

Determinations of suspended sediment concentrations from multiple day landsat and AVHRR data

Cited by 27 publications

References 5 publications

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary, USA

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary, USA

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

AN ALGORITHM FOR ESTIMATING SURFACE SUSPENDED SEDIMENT CONCENTRATIONS WITH LANDSAT MSS DIGITAL DATA¹

Contact Info

Product

Resources

About

Determinations of suspended sediment concentrations from multiple day landsat and AVHRR data

Cited by 27 publications

References 5 publications

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary, USA

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary, USA

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

AN ALGORITHM FOR ESTIMATING SURFACE SUSPENDED SEDIMENT CONCENTRATIONS WITH LANDSAT MSS DIGITAL DATA1

Contact Info

Product

Resources

About

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

AN ALGORITHM FOR ESTIMATING SURFACE SUSPENDED SEDIMENT CONCENTRATIONS WITH LANDSAT MSS DIGITAL DATA¹