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Geospatial big data handling theory and methods: A review and research challenges

期刊

出版社

ELSEVIER
DOI: 10.1016/j.isprsjprs.2015.10.012

关键词

Big data; Geospatial; Data handling; Analytics; Spatial modeling; Review

资金

  1. National Science and Engineering Research Council of Canada (NSERC) Discover Grants
  2. Engineering and Physical Sciences Research Council [EP/J004197/1, EP/G023212/1] Funding Source: researchfish
  3. EPSRC [EP/J004197/1, EP/G023212/1] Funding Source: UKRI

向作者/读者索取更多资源

Big data has now become a strong focus of global interest that is increasingly attracting the attention of academia, industry, government and other organizations. Big data can be situated in the disciplinary area of traditional geospatial data handling theory and methods. The increasing volume and varying format of collected geospatial big data presents challenges in storing, managing, processing, analyzing, visualizing and verifying the quality of data. This has implications for the quality of decisions made with big data. Consequently, this position paper of the International Society for Photogrammetry and Remote Sensing (ISPRS) Technical Commission II (TC II) revisits the existing geospatial data handling methods and theories to determine if they are still capable of handling emerging geospatial big data. Further, the paper synthesises problems, major issues and challenges with current developments as well as recommending what needs to be developed further in the near future. (C) 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

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