Performance Comparison of Methods for Tree Species Classification in Multispectral Images
AbstractA number of methods for classification of individual trees in high resolution multispectral images have been developed. The paper provides comparative analysis of some practicable methods of such type. Classification accuracy into 5 species was tested by computer simulations with real multispectral data obtained using airborne hyperspectral sensor. Coordinates and species of individual trees were supplied for testing by field work. It is shown that classification accuracy better than 97 % can be reached by more sophisticated methods in favorable conditions. Presented results can be used to choose a classification method appropriate for the particular forest inventory task. Ill. 1, bibl. 7 (in English; abstracts in English and Lithuanian).
How to Cite
Dinuls, R., Lorencs, A., & Mednieks, I. (2011). Performance Comparison of Methods for Tree Species Classification in Multispectral Images. Elektronika Ir Elektrotechnika, 111(5), 119-122. https://doi.org/10.5755/j01.eee.111.5.371
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