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This paper explores the specifics of working with geospatial data when making decisions about the current environmental status of objects based on Earth space monitoring data. The expediency of sharing statistical data, Earth remote sensing data, and contact measurements is displayed. An analysis of the specifics of this approach to solving the problems of complex processing of multi-temporal a priori data obtained by various shooting equipment was carried out. The existing methods for combining such data are analyzed and possible options for reducing temporary resources and reducing requirements for information resources when working with large volumes of information are considered. It is appropriate to use the method of hierarchical partitioning of multi-temporal image data or images of the analyzed areas obtained at the same time, but from different satellites taking into account the specifics of the shooting equipment and subject to their correspondence to the given a priori geospatial information. One of the criteria for hierarchical partitioning is the identification of areas of greatest correspondence with a priori data with their geographical reference in satellite imagery to reduce the localization time of the corresponding zones throughout the analyzed image array. The economic application effect of this method is substantiated by reducing the computational complexity of costly pattern matching processes, as well as performance improvement of change determination algorithms in topological and geometric characteristics of these objects. An algorithm is shown for detecting changes in heterogeneity in images based on the result of overlay operations with time-differentiated satellite imagery. To confirm the adequacy of the proposed method, the results of its practical implementation are shown on the Ukraine-Poland border area. A comparative analysis of the obtained results with real data is carried out.
Czasopismo
Rocznik
Tom
Strony
103--114
Opis fizyczny
Bibliogr. 24 poz.
Twórcy
autor
- PhD Prof.; National Aerospace University - “Kharkiv Aviation Institute”, Department of Geoinformation Technologies and Space Monitoring of Earth, Faculty of rocket and space engineering, 17, Chkalova str., Kharkiv, Ukraine, 61070
autor
- PhD; National Aerospace University - “Kharkiv Aviation Institute”, Department of Geoinformation Technologies and Space Monitoring of Earth, Faculty of rocket and space engineering, 17, Chkalova str., Kharkiv, Ukraine, 61070
autor
- PhD; Director; Western Scientific Centre of the National Academy of Sciences of Ukraine and of Ministry of Education and Science of Ukraine, 4, Matejka str., Lviv, 79007
Bibliografia
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- [3] Kozoderov V. V. Egorov V. D. (2011). Raspoznavanie rastitelnosti po dannym giperspektralnogo aerozondirovaniya [Vegetation recognition according to the hyperspectral aerosensing data]. Issledovanie Zemli iz kosmosa - Earth from Space, 3, 40-48 [in Russian].
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- [5] Tarshin V.A., Sotnikov A.M., Pashenko R.E. (2014). Metod operativnoj podgotovki etalonov na osnove fraktalnoj obrabotki izobrazhenij s vysokoj obektovoj nasyshennostyu [The image set preparation for training vision system] Tehnicheskoe zrenie - Technical vision, 1(5), 2-8 [in Russian].
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- [12] Karlov D.V., Berezina S.I., Ryeznikov Yu.V., Korobeckij O.V. (2019). Vikoristannya polya fraktalnoyi rozmirnosti dlya vektorizaciyi ob’yektiv rozvidki [Age of the fractal dimension field for vectorization of intelligence objects]. Sistemi ozbroyennya i vijskova tehnika - Systems of Arms and Military Equipment, 3(59), 64-71. DOI: 10.30748/soivt.2019.59.08.
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- [15] Butenko, O.S. (2010). Scenarij alternative razvitiya izmeneniya sostoyaniya anomalnyh ekologicheskih obektov pri kompleksnom vozdejstvii vozmushenij [The scenario of alternatives to the development of the state change of anomalous ecological objects under the complex influence of disturbances]. Otkrytye informacionnyei kompyuternye integrirovannye tehnologii - Open information and computer integrated technologies, 46, 225-237.
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- [19] Basarab, M. A., Volosyuk, V. K., Goryachkin, O. V., Zelenskij, A. A., Kravchenko, V. F., Ksendzuk, A. V. et al. (2007). Cifrovaya obrabotka signalovi izobrazhenij v radiofizicheskih prilozheniya
- [Digital signal and image processing in radiophysical applications]. Moscow: FIZMATLIT.
- [20] Volosyuk, V.K., Kravchenko, V.F. (2008). Statisticheskaya teoriya radiotehnicheskih sistem distancionnogo zondirovaniya i radiolokacii [Statistical theory of radio systems for remote sensing and radar]. Moscow: FIZMATLIT.
- [21] Saaty, T. L., & Vargas, L. G. (2012). The seven pillars of the analytic hierarchy process, models, methods, concepts & applications of the analytic hierarchy process. International Series in Operations Research & Management Science, 175, 23-40, Springer 978-1- 4614-3596-9.
- [22] Jalaliyoon, N., Bakar, N. A., Taherdoost, H. (2012). Accomplishment of Critical Success Factor in Organization; Using Analytic Hierarchy Process. International Journal of Academic Research in Management, Helvetic Editions Ltd, 1(1), 1-9.
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Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d863a962-46a7-43e6-9806-fac6ea15a8b2