Mr. Eugeny Godin Profile

Eugeny Godin

at Institute for Information Transmission Problems

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Proceedings Article | 27 June 2019 Paper

GIS applications in marine research in the Black Sea

Vladimir Belokopytov, Vyacheslav Dolotov, Eugeny Godin, Andrey Ingerov, Elena Zhuk

Proceedings Volume 11174, 111740R (2019) https://doi.org/10.1117/12.2533434

KEYWORDS: Databases, Geographic information systems, Oceanography, Visualization, Climatology, Satellites, Satellite imaging, Meteorology, Earth observing sensors, Human-machine interfaces

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The paper is devoted to the Black sea marine information systems. FSBSI (Marine Hydrophysical Institute of RAS) has gained a great experience in their development. A special feature of marine GISs is that in many cases the multidisciplinary and multi-component character of scientific oceanology leads to creating narrower specialized software tools to operate oceanographic data. At the same time, the accuracy of the information system representation of the processes taking place in the marine environment and in the sea – land interactive zone is determined in a considerable degree by the comprehensiveness and quality of databases in use. While creating the GISs for the Black sea, MHI uses as an information basis the Black sea database containing more than 160,000 oceanographic stations made so far since 1890. More than 80 per cent of the data have passed the quality check procedure. However, a number of GISs, for their successful operating, demand more parameters than the Black Sea database includes. This can be exemplified by the structure of the software used in the Geoinformation system of the Russian Black sea coastal zone. The database providing operation of the Specialized GIS for beach cadastral evaluation also has its peculiarities. The specific aspects of structure and functionality of the above mentioned and some other GISs created in MHI are described. The immediate objectives are identified both to create a comprehensive universal system for a wide range of researchers, with an optimized query system while addressing the integrated database, and to develop methods of spatial data sharing which allow gaining access to shared databases of the existing applied specialized systems.

Proceedings Article | 12 August 2016 Paper

PERSEUS ODV QC software

Andrey Ingerov, Alexey Khaliulin, Eugeny Godin, Elena Zhuk, Elena Isaeva, Isaac Gertman, George Zodiatis, Andreas Nikolaidis

Proceedings Volume 9688, 96881O (2016) https://doi.org/10.1117/12.2241647

KEYWORDS: Climatology, Chronology, Tolerancing, Oceanography, Oxygen, Error analysis, Databases, Reliability, Geoinformatics, Data centers

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The PERSEUS ODV QC Utility has been developed in the framework of the PERSEUS project.[1] The QC Utility implements a QC procedure for ODV files and assigns QC flags to metadata and data values according to the SEADATANET vocabulary L20. The QC procedure results are QC flags in an ODV file and a log file with a list of possible errors. The QC Utility can operate both in the window and console modes. The QC procedure includes a set of metadata and data quality tests. The metadata tests are: location check, date/time (including velocity and chronology) check and sea depth check. The data tests are based on check arrays (climate, statistics, parameter ranges and thresholds for spikes and gradients check) for sub-regions (local) or the entire region (regional). These arrays are assigned to the P02 parameter codes. The P01 codes are not used because of their superfluity (many codes correspond to the same parameter). The P02 vocabulary is more suitable but it does not provide identification of all parameters. The QC Utility gives a possibility of extending the P02 codes list to identify the parameters more correctly. Data tests include sounding value check (including order check), climatic check (if climatic arrays for the parameter are available), statistic check (if statistic arrays for the parameter are available), range check (if ranges for the parameter are available), fixing density inversions for hydrological data, fixing spikes (if corresponding thresholds for the parameter are available), gradient check (if corresponding thresholds for the parameter are available).

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