Interpolating single-beam data for sea bottom GIS modelling

Alcaras, Emanuele

doi:10.30534/ijeter/2020/50822020

Cited by 7 publications

(4 citation statements)

References 28 publications

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“…Three-dimensional models include digital elevation models (DEMs) that are typically used to visualize the variation of the Earth's surface [7] and produced through many procedures such as remote sensing, photogrammetry, and land surveying [8]. A continuous representation of the examined part of the Earth surface is typically generated using appropriate interpolators that can be applied to topographic data as well as to hydrographic data [9].…”

Section: Introductionmentioning

confidence: 99%

The Influence of Interpolated Point Location and Density on 3D Bathymetric Models Generated by Kriging Methods: An Application on the Giglio Island Seabed (Italy)

2022

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In relation to 3D bathymetric modelling, this article aims to analyze the performance of Kriging approaches in dependence of the location and density of the measured depth points. The experiments were carried out on a multi-beam sonar (MBS) dataset that includes 240,000 soundings covering a sea-bottom area near Giglio Island (Italy). Seven subsets were derived in random way from the initial regular MBS dataset, selecting an increasing number of points uniformly spaced. Seven models were generated for both Ordinary Kriging and Universal Kriging. Each model was submitted to leave-one-out cross-validation to define the exactness of the predictive values and compared with the initial grid to better evaluate the accuracy in dependence of the point number and dissemination. To investigate this relationship, a new index called MVI (Morphological Variation Index) was introduced as a measurement of the level of variation of seabed morphology. The results validate the efficiency of the Kriging methods and remark the influence of the dataset distribution on the 3D model, highlighting MVI as a useful index to represent the seabed variation as a unique value. Finally, in no rugged areas using 1 point every 1000 m2, the RMSE of the differences between measured and interpolated values falls below 1 m, while a further increment of soundings is required in the presence of a high level of variation of seabed morphology.

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Section: Introductionmentioning

confidence: 99%

The Influence of Interpolated Point Location and Density on 3D Bathymetric Models Generated by Kriging Methods: An Application on the Giglio Island Seabed (Italy)

2022

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“…Several interpolation methods are offered by GIS software to interpolate depth values, each of them has its own advantages and disadvantages [26], but in many cases, the most performing ones result kriging interpolators [24]. They cannot be applied in an automatic way but require to be tested, due to the specificity of the analysed surface morphology that may influence the results [27], and to be supervised by the user to set specific parameters. One of these parameters is the semi-variogram model, that is a graphical representation of the spatial correlation between the measurement points.…”

Section: Introductionmentioning

confidence: 99%

From electronic navigational chart data to sea-bottom models: Kriging approaches for the Bay of Pozzuoli

2021

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<p class="Abstract">Electronic Navigational Charts (ENCs), official databases created by a national hydrographic office and included in Electronic Chart Display and Information System (ECDIS), supply, among essential indications for safe navigation, data about sea-bottom morphology in terms of depth points and isolines. Those data are very useful to build bathymetric 3D models: applying interpolation methods, it is possible to produce a continuous representation of the seafloor for supporting studies concerning different aspects of a marine area, such as directions and intensity of currents, sensitivity of habitats and species, etc. Many interpolation methods are available in literature for bathymetric data modelling: among them kriging ones are extremely performing, but require deep analysis to define input parameters, i.e. semi-variogram models. This paper aims to analyze kriging approaches for depth data concerning the Bay of Pozzuoli. The attention is focused on the role of semi-variogram models for Ordinary and Universal kriging. Depth data included in two ENCs, namely IT400129 and IT400130, are processed using Geostatistical Analyst, an extension of ArcGIS 10.3.1 (ESRI). The results testify the relevance of the choice of the mathematical functions of the semi-variogram: Stable Model supplies, for this case study, the best performance in terms of depth accuracy for both Ordinary and Universal kriging.</p>

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“…Анализ применения различных методов интерполяции при построении цифровых моделей рельефа дна проводился неоднократно: [3], [4], [5], [6], [7] и др. Результаты оценки точности моделирования методом интерполяции показали, что биквадратные сплайн-методы позволяют создавать цифровые модели рельефа с наименьшими отклонениями [8].…”

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Analysis of the Accuracy of Interpolation Methods in the Process of Bathymetric Mapping of Inland Waterways

Ratner¹

2021

Vestnik GUMRF imeni admirala S. O. Makarova

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The accuracy of various interpolation methods, used by specialists when working manually or technically implemented in software when plotting bottom relief on navigation maps of inland waterways, namely nearest neighbor interpolation, triangle based interpolation, bilinear interpolation and biquadratic spline interpolation, is analyzed in the paper. The study was conducted during the process of creating an electronic navigational chart of the Northern Dvina River. The aim of the study is to determine the interpolation method that guarantees the minimum deviation of the calculated values from the original values and the rendering of the least number of artefacts. In existing cartographic and geoinformation software, only interpolation methods based on regular grid calculations are used. In this study interpolation is performed on an irregular grid since depth sounding is carried out using a single beam echo sounder, and the depth grids obtained using this type of equipment are always irregular. This makes it possible to ensure the highest possible accuracy of the initial measurement during interpolation. The accuracy of the performed interpolation is verified by dividing all depths into two parts (longitudinal and transverse tacks) and calculating the depth values at longitudinal tacks using interpolation. The maximum discrepancies of up to 50 cm are detected when performing nearest neighbor interpolation. The minimum discrepancies of less than 10 cm are detected during biquadratic spline interpolation. According to the results of the study, biquadratic spline interpolation is the best method for building digital models of the bottom relief that can then be used to plot bathymetry on navigational charts.

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Interpolating single-beam data for sea bottom GIS modelling

Cited by 7 publications

References 28 publications

The Influence of Interpolated Point Location and Density on 3D Bathymetric Models Generated by Kriging Methods: An Application on the Giglio Island Seabed (Italy)

The Influence of Interpolated Point Location and Density on 3D Bathymetric Models Generated by Kriging Methods: An Application on the Giglio Island Seabed (Italy)

From electronic navigational chart data to sea-bottom models: Kriging approaches for the Bay of Pozzuoli

Analysis of the Accuracy of Interpolation Methods in the Process of Bathymetric Mapping of Inland Waterways

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