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, A.
AU - Cheng, Tao
PY - 2016/5/1
Y1 - 2016/5/1
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 - https://ezproxy2.utwente.nl/login?url=https://doi.org/10.1016/j.isprsjprs.2015.10.012
UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2016/isi/stein_geo.pdf
U2 - 10.1016/j.isprsjprs.2015.10.012
DO - 10.1016/j.isprsjprs.2015.10.012
M3 - Short survey
AN - SCOPUS:84949294051
SN - 0924-2716
VL - 115
SP - 119
EP - 133
JO - ISPRS journal of photogrammetry and remote sensing
JF - ISPRS journal of photogrammetry and remote sensing
ER -