Land use image classification through optimum-path forest clustering
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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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 |