A New Cloud Computing Architecture for the Classification of Remote Sensing Data

Victor Andres Ayma Quirita, Gilson Alexandre Ostwald Pedro Da Costa, Patrick Nigri Happ, Raul Queiroz Feitosa, Rodrigo Da Silva Ferreira, Dario Augusto Borges Oliveira, Antonio Plaza

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

43 Citas (Scopus)

Resumen

This paper proposes a new distributed architecture for supervised classification of large volumes of earth observation data on a cloud computing environment. The architecture supports distributed execution, network communication, and fault tolerance in a transparent way to the user. The architecture is composed of three abstraction layers, which support the definition and implementation of applications by researchers from different scientific investigation fields. The implementation of architecture is also discussed. A software prototype (available online), which runs machine learning routines implemented on the cloud using the Waikato Environment for Knowledge Analysis (WEKA), a popular free software licensed under the GNU General Public License, is used for validation. Performance issues are addressed through an experimental analysis in which two supervised classifiers available in WEKA were used: random forest and support vector machines. This paper further describes how to include other classification methods in the available software prototype.

Idioma originalInglés
Páginas (desde-hasta)409-416
Número de páginas8
PublicaciónIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volumen10
N.º2
DOI
EstadoPublicada - feb. 2017
Publicado de forma externa

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