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Collaborative Computing: Networking, Applications, and Worksharing. 11th International Conference, CollaborateCom 2015, Wuhan, November 10-11, 2015, China. Proceedings

Research Article

Exploration of Applying Crowdsourcing in Geosciences: A Case Study of Qinghai-Tibetan Lake Extraction

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  • @INPROCEEDINGS{10.1007/978-3-319-28910-6_32,
        author={Jianghua Zhao and Xuezhi Wang and Qinghui Lin and Jianhui Li},
        title={Exploration of Applying Crowdsourcing in Geosciences: A Case Study of Qinghai-Tibetan Lake Extraction},
        proceedings={Collaborative Computing: Networking, Applications, and Worksharing. 11th International Conference, CollaborateCom 2015, Wuhan, November 10-11, 2015, China. Proceedings},
        proceedings_a={COLLABORATECOM},
        year={2016},
        month={2},
        keywords={Crowdsourcing Geoscientific data process GSCloud Qinghai-Tibetan lake extraction},
        doi={10.1007/978-3-319-28910-6_32}
    }
    
  • Jianghua Zhao
    Xuezhi Wang
    Qinghui Lin
    Jianhui Li
    Year: 2016
    Exploration of Applying Crowdsourcing in Geosciences: A Case Study of Qinghai-Tibetan Lake Extraction
    COLLABORATECOM
    Springer
    DOI: 10.1007/978-3-319-28910-6_32
Jianghua Zhao1,*, Xuezhi Wang1,*, Qinghui Lin1,*, Jianhui Li1,*
  • 1: Chinese Academy of Sciences
*Contact email: zjh@cnic.cn, wxz@cnic.cn, lqh@cnic.cn, lijh@cnic.cn

Abstract

With the emerging of vast quantities of geospatial data, large temporal and spatial scale of data are used in geosciences research nowadays. As a lot of data processing tasks such as image interpretation are hard to be processed automatically, and the data process workload is huge, crowdsourcing is studied as a supplement tool of cloud computing technology and advanced algorithms. This paper outlines the procedure and methodology of applying crowdsourcing in geoscientific data process. And based on the GSCloud platform, a case study of Qinghai-Tibetan Lake Extraction task has been carried out to explore the feasibility of the application of crowdsourcing in geosciences. By analyzing the case, the paper summarizes the problems and characteristics, and advantages and challenges are also presented at last.

Keywords
Crowdsourcing Geoscientific data process GSCloud Qinghai-Tibetan lake extraction
Published
2016-02-09
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-319-28910-6_32
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