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Computer Optics, 2018, Volume 42, Issue 4, Pages 695–703
DOI: https://doi.org/10.18287/2412-6179-2018-42-4-695-703
(Mi co551)
 

This article is cited in 4 scientific papers (total in 4 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

An algorithm for mapping flooded areas through analysis of satellite imagery and terrestrial relief features

O. A. Efremova, Yu. N. Kunakov, S. V. Pavlov, A. Kh. Sultanov

Ufa State Aviation Technical Univercity, Ufa, Russia
Full-text PDF (688 kB) Citations (4)
References:
Abstract: We address a problem of the joint processing of digital maps of the earth surface and satellite imagery of flooded areas as part of the software intended to help authorities to respond to emergency situations. The problem of mapping flooded areas is solved based on the use of satellite images and GIS technologies. This paper describes an algorithm for mapping areas submerged by flooded rivers based on radar satellite images and analysis of characteristic relief features, allowing one to improve the accuracy of the image geolocation with a small number of reference points. The experimental studies demonstrate that using the algorithm proposed, the alignment accuracy of the river water surface obtained from a satellite image and from a digital topographic map has increased by 40
Keywords: spatial data, flooded areas, space images, reference points, digital maps, software complex, algorithm for processing spatial data.
Received: 05.10.2017
Accepted: 29.07.2018
Document Type: Article
Language: Russian
Citation: O. A. Efremova, Yu. N. Kunakov, S. V. Pavlov, A. Kh. Sultanov, “An algorithm for mapping flooded areas through analysis of satellite imagery and terrestrial relief features”, Computer Optics, 42:4 (2018), 695–703
Citation in format AMSBIB
\Bibitem{EfrKunPav18}
\by O.~A.~Efremova, Yu.~N.~Kunakov, S.~V.~Pavlov, A.~Kh.~Sultanov
\paper An algorithm for mapping flooded areas through analysis of satellite imagery and terrestrial relief features
\jour Computer Optics
\yr 2018
\vol 42
\issue 4
\pages 695--703
\mathnet{http://mi.mathnet.ru/co551}
\crossref{https://doi.org/10.18287/2412-6179-2018-42-4-695-703}
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  • https://www.mathnet.ru/eng/co/v42/i4/p695
  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    Abstract page:177
    Full-text PDF :79
    References:24
     
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