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CrossRef 2014 2 sitasi

Automatic classification algorithm of quick bird images in the problem of evaluating of forest completeness

Institute of Computational Technologies MES RK A. Terehov N. Makarenko Institute of Computational Technologies MES RK I. Pak +1 lainnya
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Abstrak

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.

Penulis (6)

I

Institute of Computational Technologies MES RK

A

A. Terehov

N

N. Makarenko

I

Institute of Computational Technologies MES RK

I

I. Pak

I

Institute of Computational Technologies MES RK

Format Sitasi

APA MLA BibTeX
RK, I.o.C.T.M., Terehov, A., Makarenko, N., RK, I.o.C.T.M., Pak, I., RK, I.o.C.T.M. (2014). Automatic classification algorithm of quick bird images in the problem of evaluating of forest completeness. https://doi.org/10.18287/0134-2452-2014-38-3-580-583

Akses Cepat

Lihat di Sumber doi.org/10.18287/0134-2452-2014-38-3-580-583
Informasi Jurnal
Tahun Terbit
2014
Bahasa
en
Total Sitasi
2×
Sumber Database
CrossRef
DOI
10.18287/0134-2452-2014-38-3-580-583
Akses
Terbatas