Seasonal Separation of African Savanna Components Using Worldview-2 Imagery: A Comparison of Pixel- and Object-Based Approaches and Selected Classification Algorithms

Separation of savanna land cover components is challenging due to the high heterogeneity of this landscape and spectral similarity of compositionally different vegetation types. In this study, we tested the usability of very high spatial and spectral resolution WorldView-2 (WV-2) imagery to classify...

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Detalles Bibliográficos

Principais autores:	Żaneta Kaszta, Ruben Van De Kerchove, Abel Ramoelo, Moses Azong Cho, Sabelo Madonsela, Renaud Mathieu, Eléonore Wolff
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2016-09-01
Series:	Remote Sensing
Assuntos:	land cover classifiers random forest (RF) support vector machines (SVM) classification and regression trees (CART) maximum likelihood (ML) k-nearest neighbor (k-NN)
Acceso en liña:	http://www.mdpi.com/2072-4292/8/9/763
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