Novosibirsk State University Journal of Information Technologies
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ISSN 2410-0420 (Online), ISSN 1818-7900 (Print)

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All Issues >> Contents: Volume 15, Issue No 4 (2017)

Spectral-Spatial Classification of Vegetative Cover Types Using Hyperspectral Data
Mark Aleksandrovich Guryanov, Sergey Mihaylovich Borzov

Institute of Automation and Electrometry SB RAS
Novosibirsk State University

DOI: DOI 10.25205/1818-7900-2017-15-4-14-21
UDC code: 528.72:004.93

The article is devoted to the effectiveness research of controlled spectral-spatial classification of hyperspectral data methods in distinguishing vegetation types (agricultural cropes). A number of approaches to increasing the classification accuracy by considering the pixels’ vicinity on different stages of data processing have been compared using the example of the test image fragment, which was taken during the AVIRIS program. It was shown that method combining spatial processing of initial images with postprocessing of generated classification maps renders to be the most effective.

Key Words
remote sensing, hyperspectral images, surface type classification, spectral and spatial features

How to cite:
Guryanov M. A., Borzov S. M. Spectral-Spatial Classification of Vegetative Cover Types Using Hyperspectral Data // Vestnik NSU Series: Information Technologies. - 2017. - Volume 15, Issue No 4. - P. 14-21. - DOI 10.25205/1818-7900-2017-15-4-14-21. - ISSN 1818-7900. (in Russian).

Full Text in Russian

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Publication information
Main title Vestnik NSU Series: Information Technologies, Volume 15, Issue No 4 (2017).
Parallel title: Novosibirsk State University Journal of Information Technologies Volume 15, Issue No 4 (2017).

Key title: Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriâ: Informacionnye tehnologii
Abbreviated key title: Vestn. Novosib. Gos. Univ., Ser.: Inf. Tehnol.
Variant title: Vestnik NGU. Seriâ: Informacionnye tehnologii

Year of Publication: 2017
ISSN: 1818-7900 (Print), ISSN 2410-0420 (Online)
Publisher: Novosibirsk State University Press
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