Actas de congresos
Automatic landslide recognition through Optimum-Path Forest
Fecha
2012-12-01Registro en:
International Geoscience and Remote Sensing Symposium (IGARSS), p. 6228-6231.
10.1109/IGARSS.2012.6352681
WOS:000313189406055
2-s2.0-84873124352
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.