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Geoinformatika 2018; 2(66) : 24-33

УДК 626/628:528.574

 GEOINFORMATION TECHNOLOGY OF THE BLACK SEA SPACE MONITORING USING NOAA SNAPSHOTSV.

M. Yeremeev1, G.Y. Krasovsky2, T.S. Kukovskaya1, V.V. Radchuk3, V.V. Radchuk3

1 Department of Marine Geology and Sedimentary Ore-Formation, NAS of Ukraine, 55-b Gonchara St., 01054, Kyiv, Ukraine
2 M.E. Zhukovsky National Aerospace University “Kharkiv Aviation Institute”, st. Chkalov, 17, Kharkiv 61070, Ukraine, e-mail: g.krasovskiy@khai.edu
3 Institute of Telecommunications and Global Information Space, NAS of Ukraine, 13,  Chokolivskiy boulevard, Kyiv, 03186, Ukraine, e-mail: valentyn.radchuk@gmail.com

Purpose. The research aims to find the ways of improving of the Black Sea water area monitoring based on the remote sensing methods (the Earth Remote Sensing) and geoinformation systems (GIS).
Design/methodology/approach. The article presents the findings of the study. In accordance with the research purpose the study has created and tested original methodology for processing remote sensing data received from NOAA satellites.Thus, we have formed preliminary requirements to the images with respect to the current tasks. For example, in order to determine the process of water blooming, it is sufficient to use images of low spatial resolution in one or several spectral channels, and delineation of certain sections of the sea can be carried out according to the medium and high resolution data. The analysis of the internal marine erosion process requires medium and high spatial resolution data, but low spatial resolution data can be used to determine the location of this process. The study has shown that identification of the point pollution processes (such as river runoff) can be carried out by using low-resolution space imagery materials provided the territorial extent of the runoff “tongue” is more than 1 km. Moreover, the analysis of exact lineaments and internal distribution of chemicals should be carried out using medium and high resolution ERS data.
Findings. Space imagery materials potential having been identified, the study specified several areas of low resolution images application for the purpose of marine waters monitoring. These include identification and analysis of water blooming; identification of shore erosion processes; and identification and primary analysis of point marine pollution sources.The Earth Remote Sensing data classification algorithm is based on brightness characteristics of the data obtained. Multichannel satellite images reveal brightness characteristics showing the inhomogeneity of the sea surface according to various characteristics – it can be water column chemical composition, density of micro particles, temperature differences, etc. At the first stage of such data processing, it is important to identify the differences in brightness characteristics in each survey channel. The general classification algorithm includes the main and auxiliary stages. The above scheme of NOAA satellites images processing implementation is based on a constant analysis of real data, allowing us to determine the necessary and most effective methods of their processing. At this stage, the results of classification are reflected in color scale, where color change means change in the characteristics of the sea surface. In order to determine the exact classification groups, it is necessary to analyze the space survey data using the results of ground-based measurements. It is essential for the development of the objects recognizing algorithm based on the ERS data. The research considers the possibilities of the developed algorithm for the ERS data classification, using the example of NOAA satellites images of the Black Sea surface obtained in summer 2016.
Practical value/implications. The above information technology using NOAA satellites images is proposed to address practical issues of studying both natural processes and the processes that arise as a result of anthropogenic influences. It also aims to facilitate the informational support of the tasks of the Black Sea environmental safety management and rational use of its natural resources.

Keywords: GIS technology, ecological monitoring, vector map, sea surface.

 

The full text of papers

 

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