IDEAS home Printed from https://ideas.repec.org/a/igg/jdst00/v7y2016i1p1-14.html
   My bibliography  Save this article

Streaming Remote Sensing Data Processing for the Future Smart Cities: State of the Art and Future Challenges

Author

Listed:
  • 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)

  • Yechao Sun

    (China Centre for Resources Satellite Data and Application, Beijing, China)

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.

Suggested Citation

  • Xihuang Sun & Peng Liu & Yan Ma & Dingsheng Liu & Yechao Sun, 2016. "Streaming Remote Sensing Data Processing for the Future Smart Cities: State of the Art and Future Challenges," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 7(1), pages 1-14, January.
  • Handle: RePEc:igg:jdst00:v:7:y:2016:i:1:p:1-14
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJDST.2016010101
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jdst00:v:7:y:2016:i:1:p:1-14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.