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Information Services of Big Remote Sensing Data

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Big Scientific Data Management (BigSDM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11473))

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Abstract

With the rapid development of earth-observation technologies, different kinds of remote-sensing data are available, including SAR, multi-spectral optical data and hyper-spectral optical data. Remote sensing is already in an era of big data, which results in great challenges of information services. On the one hand, the potential value behind remote-sensing data has not yet been effectively mined for the thematic applications; on the other hand, for some emergency applications such as quick response of natural disasters (earthquake, forest fires, etc.), remote-sensing data and its derived information should be instantly processed and provided. However, the traditional data service mode of remote sensing is unable to meet the needs of such kind of applications. This paper proposes a concept of information services for big remote sensing data based on the needs of remote-sensing applications. The challenges of a big remote sensing data service are first discussed, and then the concept, framework, and key technologies of information service for big remote sensing data are also addressed.

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19090300), the National Natural Science Foundation of China (61731022 and 61701495), the Open Research Fund of Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (No. 2016LDE006), the National Key Research and Development Programs of China (Grant No. 2016YFA0600302 and 2016YFB0502502), the Hainan Provincial Department of Science and Technology under the grant No. ZDKJ2016021, ZDKJ2016015-1 and ZDKJ2017009. The authors thank the anonymous reviewers for their valuable suggestions and comments.

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Author information

Authors and Affiliations

  1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China

    Guojin He, Guizhou Wang, Tengfei Long, Huichan Liu, Weili Jiao, Wei Jiang, Ranyu Yin, Zhaoming Zhang, Wanchun Leng, Yan Peng, Xiaomei Zhang & Bo Cheng

  2. Key Laboratory of Earth Observation Hainan Province, Hainan, 572029, China

    Guojin He, Guizhou Wang, Tengfei Long, Huichan Liu, Weili Jiao, Zhaoming Zhang, Yan Peng, Xiaomei Zhang & Bo Cheng

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Wei Jiang, Ranyu Yin & Wanchun Leng

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  1. Guojin He
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Correspondence to Guojin He .

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Editors and Affiliations

  1. CNIC, CAS, Beijing, China

    Jianhui Li

  2. Renmin University of China, Beijing, China

    Xiaofeng Meng

  3. Centrum Wiskunde and Informatica, Amsterdam, The Netherlands

    Ying Zhang

  4. CNIC, CAS, Beijing, China

    Wenjuan Cui

  5. Tsinghua University, Beijing, China

    Zhihui Du

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He, G. et al. (2019). Information Services of Big Remote Sensing Data. In: Li, J., Meng, X., Zhang, Y., Cui, W., Du, Z. (eds) Big Scientific Data Management. BigSDM 2018. Lecture Notes in Computer Science(), vol 11473. Springer, Cham. https://doi.org/10.1007/978-3-030-28061-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-28061-1_4

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