ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


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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