Classifiers for Vegetation and Forest Mapping with Low Resolution Multiespectral Imagery

Authors:
Marcos Ferreiro-Armán;Lourenço P. Bandeira;Julio Martín-Herrero;Pedro Pina
Affiliations:
Dep. de Teoría do Sinal e Comunicacións, ETSET, Universidade de Vigo, Spain;CERENA, Insituto Superior Técnico, Lisboa, Portugal;Dep. de Teoría do Sinal e Comunicacións, ETSET, Universidade de Vigo, Spain;CERENA, Insituto Superior Técnico, Lisboa, Portugal
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Year:
2007

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Abstract

This paper deals with the evaluation of the performance of a set of classifiers on multispectral imagery with low dimensionality and low spatial and spectral resolutions. The original Landsat TM images and other 4 transformed sets are classified by 5 supervised and 2 unsupervised methods. The results for 7 land cover classes are compared and the performances of the methods for each set of input data are discussed.