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Streaming Remote Sensing Data Processing for the Future Smart Cities: State of the Art and Future Challenges
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Author(s): Xihuang Sun (Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China), Peng Liu (Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China), Yan Ma (Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China), Dingsheng Liu (Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing, China)and Yechao Sun (China Centre for Resources Satellite Data and Application, Beijing, China)
Copyright: 2016
Volume: 7
Issue: 1
Pages: 14
Source title:
International Journal of Distributed Systems and Technologies (IJDST)
Editor(s)-in-Chief: Nik Bessis (Edge Hill University, UK)
DOI: 10.4018/IJDST.2016010101
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Abstract
The explosion of data and the increase in processing complexity, together with the increasing needs of real-time processing and concurrent data access, make remote sensing data streaming processing a wide research area to study. This paper introduces current situation of remote sensing data processing and how timely remote sensing data processing can help build future smart cities. Current research on remote sensing data streaming is also introduced where the three typical and open-source stream processing frameworks are introduced. This paper also discusses some design concerns for remote sensing data streaming processing systems, such as data model and transmission, system model, programming interfaces, storage management, availability, etc. Finally, this research specifically addresses some of the challenges of remote sensing data streaming processing, such as scalability, fault tolerance, consistency, load balancing and throughput.
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