The Reduction Method of Bathymetric Datasets that Preserves True Geodata

Remote Sensing

Andrzej Stateczny¹  Jacek Lubczonek²  Marta Wlodarczyk-Sielicka² 

[1] Department of Geodesy, Gdansk University of Technology, 80-233 Gdansk, Poland;Institute of Geoinformatics, Department of Navigation, Maritime University of Szczecin, 70-500 Szczecin, Poland;

关键词: big data applications;    data processing;    data visualization;    neural networks;    reduction;    coastal waters;   

DOI  :  10.3390/rs11131610

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown