Effect of Gridding Method on Digital Terrain Model Profile Data Based on Scattered Data

Yanalak, Mustafa

doi:10.1061/(asce)0887-3801(2003)17:1(58)

Cited by 34 publications

(18 citation statements)

References 17 publications

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“…Contemporary hydrographic and GIS software allow for such a visualisation, but the image is usually created in a simplest way -for each measurement point a corresponding pixel is set in the output image (presented on screen) [11]. Since we are dealing with huge amount of data (many millions of points) with high density, usually the imaged area appears solid, without the possibility to distinguish particular points (see Fig.…”

Section: Introductionmentioning

confidence: 99%

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Visualisation of Multibeam Echosounder Measurement Data

Maleika

Czapiewski

2013

Lecture Notes in Computer Science

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Abstract. During a sea survey session performed using a multibeam echosounder millions of measurement points are generated. Sea surveys should be carried out in such a way, that the maximum accuracy of created seabed models (DTM) is achieved and the standards specified by the IHO S-44 guidelines are met. One of the requirements is so called full sea floor search, which means the ability of a system to detect all the cubic features at least 1 m in size. Spatial distribution of measurement points is irregular and the distances between closest data points are varying, depending on many factors (on survey parameters, depth or distance between the beam and the vessel). Due to those reasons, it is difficult for the users of hydrographic systems to evaluate the degree of coverage of seabed by measurement points, and therefore to confirm fulfilment of the normative requirements. As a solution we propose visualisation methods for measurement data collected in sea surveys. Specific features of such a visualisation are explained and a method for creating the images is presented, along with some exemplary results.

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Section: Introductionmentioning

confidence: 99%

“…The cardinality and density of the collected data depends on the parameters of the recording device (i.e. the echosounder parameters: number of beams, sampling frequency and beam width; and the survey parameters: speed of the measurement vessel, number of survey tracks, and survey track configuration) [6,11].…”

Section: Introductionmentioning

confidence: 99%

Visualisation of Multibeam Echosounder Measurement Data

Maleika

Czapiewski

2013

Lecture Notes in Computer Science

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“…However, for large data sets it seems more justified to use grid (Brasington and Richards 1998;Falcao et al 2013;Jalving 1999;Luo et al 2014;Yanalak 2003).…”

Section: Introductionmentioning

confidence: 99%

The influence of the grid resolution on the accuracy of the digital terrain model used in seabed modeling

Maleika

2014

Mar Geophys Res

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Modern digital terrain models (DTM) are widely used in the exploration of water areas. The models are often based on bathymetric data from a multibeam echosounder. DTM creators should properly select model parameters, firstly the grid resolution. High grid resolution enables creating very accurate models, however, they require high computing power and the data gathered in the grid occupy much more memory space. Low grid resolution means significantly less data describing the model, but, naturally, its accuracy will also be lower. The author proposes a method permitting to examine the accuracies of DTMs that depend on adopted grid resolution. Further the article will present search for an accurate grid resolution for three selected real surfaces of the seabed. The obtained results were visualized and interpreted. The author also proposes tips to be used while creating DTMs. Conclusions from the research may be helpful in digital terrain modeling of the seabed.

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“…Usually, the optimal method of interpolation depends on the Root Mean Square Error (RMSE) of the output. In most studies the comparison of interpolation methods and the selection of the optimal methods are used to achieve higher accuracy [16] [43]. In this paper, AI techniques such as NN and GA were examined to optimise the interpolation methods and the creation of DEM on the samples.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Role of Genetic Algorithms and Artificial Neural Networks for Interpolation of Elevation in Geoinformation Models

Bagheri

Sadjadi

Sadeghian³

2013

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:One of the most significant tools to study many engineering projects is three-dimensional modelling of the Earth that has many applications in the Geospatial Information System (GIS), e.g. creating Digital Train Modelling (DTM). DTM has numerous applications in the fields of sciences, engineering, design and various project administrations. One of the most significant events in DTM technique is the interpolation of elevation to create a continuous surface. There are several methods for interpolation, which have shown many results due to the environmental conditions and input data. The usual methods of interpolation used in this study along with Genetic Algorithms (GA) have been optimised and consisting of polynomials and the Inverse Distance Weighting (IDW) method. In this paper, the Artificial Intelligent (AI) techniques such as GA and Neural Networks (NN) are used on the samples to optimise the interpolation methods and production of Digital Elevation Model (DEM). The aim of entire interpolation methods is to evaluate the accuracy of interpolation methods. Universal interpolation occurs in the entire neighbouring regions can be suggested for larger regions, which can be divided into smaller regions. The results obtained from applying GA and ANN individually, will be compared with the typical method of interpolation for creation of elevations. The resulting had performed that AI methods have a high potential in the interpolation of elevations. Using artificial networks algorithms for the interpolation and optimisation based on the IDW method with GA could be estimated the high precise elevations.

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Effect of Gridding Method on Digital Terrain Model Profile Data Based on Scattered Data

Cited by 34 publications

References 17 publications

Visualisation of Multibeam Echosounder Measurement Data

Visualisation of Multibeam Echosounder Measurement Data

The influence of the grid resolution on the accuracy of the digital terrain model used in seabed modeling

Exploring the Role of Genetic Algorithms and Artificial Neural Networks for Interpolation of Elevation in Geoinformation Models

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