Sea bottom topography with X-band SLAR: the relation between radar imagery and bathymetry

Vogelzang, J.; Wensink, G.J.; Loor, G.P. de; Peters, Herman; Pouwels, H.

doi:10.1080/01431169208904242

Cited by 39 publications

(14 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results show the potential of TOPSAR data for ocean bathymetry reconstruction where TOPSAR L HH band backscatter across bathymetry signature pixels agrees satisfactorily with previous published results (Vogelzang et al 1992;Inglada and Garello 1999;Marghany et al, 2007). This is due to the fact that the ocean signature of the boundary is clear in the brightness of a radar return, since the backscatter tends to be proportional to wave height (Vogelzang et al 1992). In Cband with VV polarization, this feature is clearly weaker than at L-band with HH polarization.…”

Section: Three-dimensional Ocean Bathymetry From Topsar Datasupporting

confidence: 79%

“…They found that a single set of coefficients derived from a set of IKONOS images produces the good performance with an aggregate RMS error of + 2.3 m which is higher than bathymetry retrieved from SAR (Hesselmans et al 2000). Coastal bathymetry mapping by using optical remote sensing data, however, can be only fully utilized in the clearest water, and considerably less in turbid water (Vogelzang et al, 1992). Indeed, as the different wavelengths pass through the water column they become attenuated by the interaction with suspended particles in water (Mills, 2008).…”

Section: Principle Of Sar Ocean Bathymetry Imagingmentioning

confidence: 99%

“…Then, the continuity equation is used to estimate the water depth as given by Vogelzang et al (1992) . {( ) (0, )} 0…”

Section: Topsarmentioning

confidence: 99%

“…In contrast, conventional techniques such as single-or multi-beam ship-borne echoes are costly and time-consuming, especially when large areas are being surveyed (Marghany et al, 2009b). The ocean bathymetry features can image by radar in coastal waters with strong tidal currents (Vogelzang et al, 1992;Vogelzang et al, 1997;Hesselmans et al, 2000. Under practical circumstances, synthetic aperture radar (SAR) is able to detect shallow ocean bathymetry features (Alpers and Hennings 1984;Shuchman et al 1985;.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

3-D Coastal Bathymetry Simulation from Airborne TOPSAR Polarized Data

Marghany¹

2012

Bathymetry and Its Applications

View full text Add to dashboard Cite

Section: Three-dimensional Ocean Bathymetry From Topsar Datasupporting

confidence: 79%

Section: Principle Of Sar Ocean Bathymetry Imagingmentioning

confidence: 99%

“…Then, the continuity equation is used to estimate the water depth as given by Vogelzang et al (1992) . {( ) (0, )} 0…”

Section: Topsarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

3-D Coastal Bathymetry Simulation from Airborne TOPSAR Polarized Data

Marghany¹

2012

Bathymetry and Its Applications

View full text Add to dashboard Cite

“…In case of microwave imagery, radar observes the backscattered variations from the sea surface, e.g. roughness caused by modulations in the wave spectrum with respect to the surface current [11]. Such variations in the current velocity at the ocean surface can be recognized because of interactions between tidal flow and bed topography.…”

Section: Introductionmentioning

confidence: 99%

A Synoptic Review on Deriving Bathymetry Information Using Remote Sensing Technologies: Models, Methods and Comparisons

Jawak¹,

Vadlamani²,

Luis³

2015

ARS

113

View full text Add to dashboard Cite

This paper discusses the bathymetric mapping technologies by means of satellite remote sensing (RS) with special emphasis on bathymetry derivation models, methods, accuracies, advantages, limitations, and comparisons. Traditionally, bathymetry can be mapped using echo sounding sounders. However, this method is constrained by its inefficiency in shallow waters and very high operating logistic costs. In comparison, RS technologies present efficient and cost-effective means of mapping bathymetry over remote and broad areas. RS of bathymetry can be categorised into two broad classes: active RS and passive RS. Active RS methods are based on active satellite sensors, which emit artificial radiation to study the earth surface or atmospheric features, e.g. light detection and ranging (LIDAR), polarimetric synthetic aperture radar (SAR), altimeters, etc. Passive RS methods are based on passive satellite sensors, which detect sunlight (natural source of light) radiation reflected from the earth and thermal radiation in the visible and infrared portion of the electromagnetic spectrum, e.g. multispectral or optical satellite sensors. Bathymetric methods can also be categorised as imaging methods and non-imaging methods. The non-imaging method is elucidated by laser scanners or LIDAR, which measures the distance between the sensor and the water surface or the ocean floor using a single wave pulse or double waves. On the other hand, imaging methods approximate the water depth based on the pixel values or digital numbers (DN) (representing reflectance or backscatter) of an image. Imaging methods make use of the visible and/or near infrared (NIR) and microwave radiation. Imaging methods are implemented with either analytical modelling or empirical modelling, or by a blend of both. This paper presents the development of bathymetric mapping technology by using RS, and discusses the state-of-the-art S. D. Jawak et al. 148bathymetry derivation methods/algorithms and their implications in practical applications.

show abstract

A review of mathematical models of river planform changes

Mosselman

1995

Earth Surf Processes Landf

View full text Add to dashboard Cite

Different mathematical models of river planform changes exist or are being developed. They are reviewed here by discussing a two-dimensional depth-averaged model, various meander models and a model for the braided Brahmaputra-Jamuna River in Bangladesh. Much emphasis is placed on topics where further research is needed. It is concluded that the models help in understanding the underlying processes, but cannot yet be considered generally valid and easy-to-use software packages. In the hands of experienced geomorphologists or river engineers, however, some of the models do already form valuable tools which allow better predictions of future river planforms.

show abstract

Sea bottom topography with X-band SLAR: the relation between radar imagery and bathymetry

Cited by 39 publications

References 14 publications

3-D Coastal Bathymetry Simulation from Airborne TOPSAR Polarized Data

3-D Coastal Bathymetry Simulation from Airborne TOPSAR Polarized Data

A Synoptic Review on Deriving Bathymetry Information Using Remote Sensing Technologies: Models, Methods and Comparisons

A review of mathematical models of river planform changes

Contact Info

Product

Resources

About