TY - JOUR

T1 - Geospatial big data handling theory and methods

T2 - A review and research challenges

AU - Li, Songnian

AU - Dragicevic, Suzana

AU - Castro, Francesc Antón

AU - Sester, Monika

AU - Winter, Stephan

AU - Coltekin, Arzu

AU - Pettit, Christopher

AU - Jiang, Bin

AU - Haworth, James

AU - Stein, Alfred

AU - Cheng, Tao

N1 - Funding information: The partial support of this study was funded by the National Science and Engineering Research Council of Canada ( NSERC ) Discover Grants awarded separately to the first and second authors. The authors thank Anthony Lee (Spatial Analysis and Modeling Laboratory, Simon Fraser University, Department of Geography) for assistance in compiling the reference database and formatting the citations.

PY - 2015/12/2

Y1 - 2015/12/2

N2 - 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.

AB - 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.

KW - Analytics

KW - Big data

KW - Data handling

KW - Geospatial

KW - Review

KW - Spatial modeling

UR - http://www.scopus.com/inward/record.url?scp=84949294051&partnerID=8YFLogxK

U2 - 10.1016/j.isprsjprs.2015.10.012

DO - 10.1016/j.isprsjprs.2015.10.012

M3 - Survey paper

AN - SCOPUS:84949294051

VL - 115

SP - 119

EP - 133

JO - ISPRS Journal of Photogrammetry and Remote Sensing

JF - ISPRS Journal of Photogrammetry and Remote Sensing

SN - 0924-2716

ER -