Automatic classification algorithm of quick bird images in the problem of evaluating of forest completeness
A.G. Terehov, N.G. Makarenko, I.T. Pak

Institute of Computational Technologies MES RK

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Full text of article: Russian language.

DOI: 10.18287/0134-2452-2014-38-3-580-583

Pages: 580-583.

Abstract:
Automated technology based on ultra-high spatial resolution (QuickBird) satellite data has been developed to estimate fraction of projective covering by crowns of trees and calculate forest integrity on the sample of Aman-Karagaisky forest in the Northern Kazakhstan. The processing algorithm is based on the threshold allocation of mask of shadows and its succeeding morphological filtering. The map of forest’s test area integrity built by Land Cover Classification System [LCCS] criteria have an accuracy of 82.5% relatively to the corresponding map based on an expert decoding.

Key words:
remote sensing, high resolution images, mask of shadows, morphological filtering, projective covering by crowns of trees, forest integrity.

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