Land use image classification through optimum-path forest clustering


Autoria(s): Pisani, R.; Riedel, P.; Ferreira, M.; Marques, M.; Mizobe, R.; Papa, J.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

16/11/2011

Resumo

Land use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.

Formato

826-829

Identificador

http://dx.doi.org/10.1109/IGARSS.2011.6049258

International Geoscience and Remote Sensing Symposium (IGARSS), p. 826-829.

http://hdl.handle.net/11449/72802

10.1109/IGARSS.2011.6049258

WOS:000297496300199

2-s2.0-80955164075

Idioma(s)

eng

Relação

International Geoscience and Remote Sensing Symposium (IGARSS)

Direitos

closedAccess

Palavras-Chave #Land use #mean shift #optimum-path forest #unsupervised classification #K-means #Landuse classifications #Mean shift #Unsupervised classification #Geology #Remote sensing
Tipo

info:eu-repo/semantics/conferencePaper