Rational Method for Correcting Sea Truth of Suspended Sediment Concentration Related to Remote Sensing

Rational Method for Correcting Sea Truth of Suspended Sediment Concentration Related to Remote Sensing PDF Author: Chin Y. Kuo
Publisher:
ISBN:
Category : Marine sediments
Languages : en
Pages : 156

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Rational Method for Correcting Sea Truth of Suspended Sediment Concentration Related to Remote Sensing

Rational Method for Correcting Sea Truth of Suspended Sediment Concentration Related to Remote Sensing PDF Author: Chin Y. Kuo
Publisher:
ISBN:
Category : Marine sediments
Languages : en
Pages : 156

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Verification of a Rational Method for Correcting the in Situ Data of Suspended Sediment Concentration Related to Remote Sensing Data Process

Verification of a Rational Method for Correcting the in Situ Data of Suspended Sediment Concentration Related to Remote Sensing Data Process PDF Author: Chin Y. Kuo
Publisher:
ISBN:
Category : Marine sediments
Languages : en
Pages : 80

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A Regression Technique for Evaluation and Quantification for Water Quality Parameters from Remote Sensing Data

A Regression Technique for Evaluation and Quantification for Water Quality Parameters from Remote Sensing Data PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 22

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Monitoring of Suspended Sediment Concentration Using Optical Methods and Remote Sensing

Monitoring of Suspended Sediment Concentration Using Optical Methods and Remote Sensing PDF Author: K. S. Albanakis
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Remote Sensing of Suspended Sediment in San Francisco Bay Using Satellite and Drone Imagery

Remote Sensing of Suspended Sediment in San Francisco Bay Using Satellite and Drone Imagery PDF Author: Joseph Henry Adelson
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Suspended sediment in San Francisco Bay affects the economic and ecological health of the estuary and its surrounding region by limiting light availability for photosynthesis, transporting contaminants, nourishing marsh restoration projects, infilling shipping channels, and providing protection to the shoreline from sea level rise via accretion on mudflats. Traditional efforts to study sediment transport phenomena have relied upon in situ measurements and numerical modeling, but these approaches have limitations. In situ measurement techniques rely on point measurements with high temporal resolution, yet they are difficult to deploy over large spatial areas. Models provide useful insight into the spatial heterogeneity of sediment processes. However, they rely on initial and boundary conditions and parameterizations that are based on observations, therefore the accuracy of models is also constrained in part by the limitations of in situ measurements. This dissertation presents remote sensing measurements from satellites and unmanned aerial vehicles (UAVs) to understand suspended sediment transport processes in estuaries like San Francisco Bay. Twelve methods for inferring suspended sediment concentration (SSC) from Landsat 7 imagery were compared using k-folds validation and assessed based on their abilities to recreate in situ SSC measurements from one meter below the surface. The best performer was the model of Nechad et al. (2010) using the red wavelength band with coefficients determined via Huber regression, with mean absolute error of 5.94 mg L-1 and bias of 0.15 mg L-1. Satellite-derived SSC observations compare well with USGS transects indicating that the method is well-suited to supplement cruise data that is costly to acquire and therefore limited in its frequency. Remote sensing measurements were aggregated by location, season, or tidal phase to understand the variability of SSC and to compare probability densities with in situ measurements. These results show that surface SSC is heightened in the shoals during summer months and has trended downward in Suisun and Grizzly Bays since 1999. Using satellite imagery from 2014-2017, remotely sensed surface SSC derived from the Nechad method was paired with bottom stress estimates based on two-dimensional hydrodynamic and fetch-limited wave models to investigate the relationship between surface SSC and flow. Observations of SSC closely fit a lognormal distribution though the shape, characterized by the modal value, depend on binning criteria including embayment, depth, and wave height. When binned by model-derived bottom shear stress, the modal value of the SSC distribution exhibited an inflection point at the critical shear stress for erosion. This suggests that remote sensing can be used to derive critical stresses that are otherwise difficult to measure. To account for the limitations of satellite imagery such as low spatial resolution and low temporal resolution (Landsat 7 overpasses occurred roughly once every 16 days), a method was developed to infer surface SSC from UAV-based imagery. While traditional remote sensing platforms take imagery at approximately a nadir viewing angle and provide multispectral images that are aligned with one another, an off-the-shelf camera aboard a UAV may not adhere to those qualities. Low cost multi-spectral cameras often include individual sensors for each band. The slight misalignment between images violates assumptions in two-band glint correction algorithms. Additionally, UAVs must tilt to fly and compensate for wind requiring images to occasionally be taken at angles more oblique than most satellite imagery. The method developed in this dissertation adapts previous techniques for sun glint correction for misaligned multispectral images and offers a novel approach to reduce the effects of camera orientation for oblique angles. During a field campaign, the UAV-based method to capture remote sensing reflectance was validated via comparison with in situ measurements made with a hyperspectral radiometer, and its ability to accurately infer SSC was verified based on in situ water samples. It was found that a polarizing filter is necessary to mitigate much of the glare on the water surface. A series of test flights were conducted to measure the surface SSC along a transect parallel to the Dumbarton Bridge during different phases of the tidal cycle. To reduce the impact of variability of incoming light, the flights were conducted over a period of 12 days at the same solar zenith angle during each day. Because the tide arrives later by roughly 50 minutes each day, consecutive daily transects over 12 days provided the variability over a tidal cycle. Cross-sectional sediment flux was computed from the remotely sensed surface SSC measurements and compared well to flux values estimated from in situ USGS observations.

Discrimination of Suspended Sediment Concentrations Using Multispectral Remote Sensing Techniques [microform]

Discrimination of Suspended Sediment Concentrations Using Multispectral Remote Sensing Techniques [microform] PDF Author: Liedtke, Jeffrey Lee
Publisher: National Library of Canada
ISBN: 9780315425897
Category : Multispectral photography
Languages : en
Pages : 238

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A Study on the Quantitative Remote Sensing Model for the Suspended Sediment Concentration in Coastal Waters with ASTER Data

A Study on the Quantitative Remote Sensing Model for the Suspended Sediment Concentration in Coastal Waters with ASTER Data PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 5

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Suspended sediment concentration (SSC) is one of the most important water quality parameters. After corrected by 6S atmospheric model, the spectral profiles of water reflectivity of ASTER data are analyzed. There is greater difference in spectral visible and near-infrared bands than that in spectral short wave infrared bands. The higher SSC is, the larger RR/RG is, in which RG and RR are the reflectivity of green band (channel 1) and red band (channel 2). So SSC may be expressed as the function of RR/RG: SSC = f(RR/RG). The quantitative remote sensing model for estimating SSC in coastal waters is founded. The model is well applied in coastal waters of the Yellow River Delta in China. Key Words- ASTER data, suspended sediment concentration, quantitative remote sensing analysis.

Remote Sensing Suspended Sediment Concentration in the Yellow River

Remote Sensing Suspended Sediment Concentration in the Yellow River PDF Author: Liqin Qu
Publisher:
ISBN:
Category :
Languages : en
Pages : 260

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Optical Remote Sensing of Suspended Sediment Concentration in Coastal Water

Optical Remote Sensing of Suspended Sediment Concentration in Coastal Water PDF Author: Zhimin Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Principles of Remote Sensing

Principles of Remote Sensing PDF Author: Lucas L. F. Janssen
Publisher:
ISBN: 9789061641834
Category : Remote sensing
Languages : en
Pages : 170

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