Electronic Journal of Polish Agricultural Universities (EJPAU) founded by all Polish Agriculture Universities presents original papers and review articles relevant to all aspects of agricultural sciences. It is target for persons working both in science and industry,regulatory agencies or teaching in agricultural sector. Covered by IFIS Publishing (Food Science and Technology Abstracts), ELSEVIER Science - Food Science and Technology Program, CAS USA (Chemical Abstracts), CABI Publishing UK and ALPSP (Association of Learned and Professional Society Publisher - full membership). Presented in the Master List of Thomson ISI.

Copyright © Wydawnictwo Akademii Rolniczej we Wroclawiu, ISSN 1505-0297

Bogoliubova A. , Tymków P. 2014. LAND COVER CHANGES AND DYNAMICS OF YUNTOLOVSKY RESERVE, EJPAU 17(3), #03.
Available Online: http://www.ejpau.media.pl/volume17/issue3/abs-03.html

ABSTRACT

In this study, the land cover types of the Yuntolovsky reserve were analyzed
on the basis of the classification results acquired using  pixel-based image
analysis approaches. Aerial images were used to carry out the image classification
and ground truth data was collected from the available maps (Soil map, Topographic
maps), field observation and from personal knowledge. In pixel-based image analysis
supervised classification was performed using the minimum distance, Mahalonobis
distance, box-classifier through ILWIS 3.31, maximum likelihood classifier.
On the other hand, pixel-based image analysis unsupervised classification was
evaluated through ILWIS 3.31 software. During the implementation, several
different sets of parameters were tested for image segmentation and the standard
nearest neighbour was used as the classifier. The results of the classified images
have shown  that the Maximum Likelihood approach gave more accurate results,
including the overall accuracy, higher producer’s and user’s accuracy
for most of the land cover classes in the studied region than those achieved
by pixel-based classification algorithms, such as: minimum distance, Mahalanobis
distance, box-classifier and cluster analyses.

Key words: landscape, remote sensing, image processing, natural heritage.

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Anna Bogoliubova
Department of Engineering Geodesy, National University of Mineral Resources (Mining University), Saint Petersburg, Russia
199106, St. Petersburg,
line 21, h. 2
Russia
email: bonya.234@gmail.com

Przemysław Tymków
Institute of Geodesy and Geoinformatics, Wrocław University of Environmental and Life Sciences, Poland
Grunwaldzka 53
50-357 Wrocław
Poland
email: przemyslaw.tymkow@igig.up.wroc.pl

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Responses to this article, comments are invited and should be submitted within three months of the publication of the article. If accepted for publication, they will be published in the chapter headed 'Discussions' and hyperlinked to the article.

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