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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 4, pp. 29-36

Comparison of methods for object-oriented and neural network classification of remote sensing data based on Landsat-5 and Orbview-3 materials

A.A. Romanov , K.A. Rubanov 
Siberian Federal University, 660041 Krasnoyarsk, Svobodniy prospect, 79
Comparative analysis of the accuracy of classification methods of remote sensing data based on object-oriented and
neural network approaches is presented. Process was carried out according to the datasets of middle and high spatial
resolution (Landsat 5 и Orbview 3) characterizing the same land surface area. It was shown that neural network algorithm
performance significantly exceeded the accuracy of the algorithm based on object-oriented approach (OOA) in
the case of Landsat datasets (92 % vs. 74 %), and insignificantly (just for 2 %) surpassed the results of the OOA for
Orbview datasets.
Keywords: remote sensing, supervised classification, neural networks, statistical algorithms, object-oriented approach, Landsat, Orbview
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