Interpolation Methods and the Accuracy of Bathymetric Seabed Models Based on Multibeam Echosounder Data

Maleika, Wojciech; Pałczyński, M.; Frejlichowski, Dariusz

doi:10.1007/978-3-642-28493-9_49

Cited by 30 publications

(15 citation statements)

References 4 publications

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“…With the assumption that the seabed topography changes smoothly along the ping and the beams reflect the change tendency (Bjørke and Nilsen 2009;Maleika et al 2012), the low-frequency part, or the trend of beams in a ping can be generally expressed by a linear function.…”

Section: Polynomial Methodsmentioning

confidence: 99%

A new method for weakening the combined effect of residual errors on multibeam bathymetric data

et al. 2014

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Multibeam bathymetric system (MBS) has been widely applied in the marine surveying for providing high-resolution seabed topography. However, some factors degrade the precision of bathymetry, including the sound velocity, the vessel attitude, the misalignment angle of the transducer and so on. Although these factors have been corrected strictly in bathymetric data processing, the final bathymetric result is still affected by their residual errors. In deep water, the result usually cannot meet the requirements of high-precision seabed topography. The combined effect of these residual errors is systematic, and it's difficult to separate and weaken the effect using traditional single-error correction methods. Therefore, the paper puts forward a new method for weakening the effect of residual errors based on the frequency-spectrum characteristics of seabed topography and multibeam bathymetric data. Four steps, namely the separation of the low-frequency and the high-frequency part of bathymetric data, the reconstruction of the trend of actual seabed topography, the merging of the actual trend and the extracted microtopography, and the accuracy evaluation, are involved in the method. Experiment results prove that the proposed method could weaken the combined effect of residual errors on multibeam bathymetric data and efficiently improve the accuracy of the final post-processing results. We suggest that the method should be widely applied to MBS data processing in deep water.

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Section: Polynomial Methodsmentioning

confidence: 99%

A new method for weakening the combined effect of residual errors on multibeam bathymetric data

et al. 2014

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“…The position of the measured depth was connected to the GPS by applying the acoustic method on an Echosounder Echotrack CVM Teledyne Odom Hydrographic Single Beam. The tool transmitted the acoustic frequencies to the bottom of the ocean waters to get the real-time depth data [12]. The obtained bathymetry data is then analyzed spatially and mathematically.…”

Section: Methodsmentioning

confidence: 99%

Numerical Hydrodynamic Wave Modelling Using Spatial Discretization in Brebes Waters, Central Java, Indonesia

Ondara¹,

Rahmawan²,

Gemilang³

et al. 2018

International Journal on Advanced Science, Engineering and Information Technology

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When the wave is moving toward the shoreline, hydrodynamic processes occurred in the waves that give an effect on the shoreline and its surrounding buildings. The process of erosion and accretion that occurred on Brebes coastal area induces certain impacts. The purpose of this study was to determine the pattern of hydro-oceanography and seabed morphology in coastal areas. Primary data obtained during field survey was employed in this study, which was processed using simulation models by applying spatial discretization method that is based on the finite volume equations to obtain the condition of waves, currents, sediment transports and tides. The results showed Brebes waters included in the category of shallow waters with slope topography, while the tidal type is a mixed tide prevailing semidiurnal. Waves were generated in the Northern Brebes then were moved towards the mainland until it deformed, leaving energy in the form of longshore current that goes into the area around the beach ridge. The time difference between high and low tide was influenced by the mass of estuary water supply from the sea as well as the mass of water from upstream to downstream. The high level of vulnerability in the coastal area requires the more effective and efficient treatment to prevent a negative impact on physical and social conditions.

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“…The processing of large such amounts of data (millions of measurement points) requires the application of specially prepared methods and properly selected processing algorithms [10,11]. There are numerous methods of determining grid based on huge datasets, the ones most frequently applied being minimum nearest neighbour, inverse distance to a power, curvature, natural neighbour, modified Shepard's method, radial basis function, triangulation with linear interpolation, moving average, kriging, and methods based on artificial intelligence [12][13][14][15][16]. These methods make use of a series of differentiated algorithms to calculate the values of interpolated parameters at node points (the depth).…”

Section: Introductionmentioning

confidence: 99%

“…Compared to other methods, DTM creation time can require as much as eight times longer as compared to the Inverse Distance to a Power method, or 20 times longer than the moving average method [18]. Therefore, kriging is commonly used for smaller datasets (hundreds of thousands of measurement points), but for larger datasets other methods are used that are significantly faster and only slightly less accurate (resulting in an error increase by approximately 0.1%) [15]. A viable question arises as to whether it is possible to optimize the generic kriging method for the purpose of processing large bathymetric datasets in the process of DTM creation.…”

Section: Introductionmentioning

confidence: 99%

Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs

Maleika

2018

Geosciences

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The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is often considered to be one of the best methods for interpolation of non-uniform spatial data, but the good results with respect to model’s accuracy come at the price of very long computational time. In this study, the optimization of the kriging method was performed for the purpose of seabed DTM creation based on millions of measurement points obtained from a multibeam echosounder device (MBES). The purpose of the optimization was to significantly decrease computation time, while maintaining the highest possible accuracy of created model. Several variants of kriging method were analysed (depending on search radius, minimum of required points, fixed number of points, and used smoothing method). The analysis resulted in a proposed optimization of the kriging method, utilizing a new technique of neighbouring points selection throughout the interpolation process (named “growing radius”). Experimental results proved the new kriging method to have significant advantages when applied to DTM estimation.

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Interpolation Methods and the Accuracy of Bathymetric Seabed Models Based on Multibeam Echosounder Data

Cited by 30 publications

References 4 publications

A new method for weakening the combined effect of residual errors on multibeam bathymetric data

A new method for weakening the combined effect of residual errors on multibeam bathymetric data

Numerical Hydrodynamic Wave Modelling Using Spatial Discretization in Brebes Waters, Central Java, Indonesia

Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs

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