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

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

来源：IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(2): 409-416.

DOI：10.1109/JSTARS.2016.2603120

• Distributed computing
• image classification
• remote sensing

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

• 出版日期2017-2
• 单位IBM