The Reduction Method of Bathymetric Datasets that Preserves True Geodata

Marta Wlodarczyk-Sielicka,Jacek Lubczonek,Andrzej Stateczny

doi:10.3390/rs11131610

Marta Wlodarczyk-Sielicka, Jacek Lubczonek + Show 1 more

Open Access

https://doi.org/10.3390/rs11131610

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Abstract

Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and the objects located on it. Information about the quality and reliability of the depth data is important, especially during coastal modelling. In-shore areas are liable to continuous transformations and they must be monitored and analyzed. Presently, bathymetric geodata are usually collected via modern hydrographic systems and comprise very large data point sequences that must then be connected using long and laborious processing sequences including reduction. As existing bathymetric data reduction methods utilize interpolated values, there is a clear requirement to search for new solutions. Considering the accuracy of bathymetric maps, a new method is presented here that allows real geodata to be maintained, specifically position and depth. This study presents a description of a developed method for reducing geodata while maintaining true survey values.

Highlights

Bathymetric data are one of basic data types used in systems modeling of phenomena occurring in coastal zones
An example is the use of bathymetry for numerical analyses related to water quality prediction in coastal waters [2] or for coastal hydrodynamics modelling [3]
Subsequent to analysis of all visualizations for the test surface No 1, it was clear that the points obtained by our reduction did meet the visual assessment criteria as they only overlapped in a few places

Summary

Introduction

Bathymetric data are one of basic data types used in systems modeling of phenomena occurring in coastal zones. The use of bathymetric data in electronic navigational charts is an important factor. The accuracy of these data in this case determines the safety of maritime transport, especially in coastal areas where shallow water is common. The authors focused on processing reduced datasets from real bathymetric measurements, which can be used in practically any system. This approach is quite different from the standard forms of modeling bathymetry from high-density data, which is usually a GRID structure

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