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Fields as a Generic Data Type for Big Spatial Data

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Geographic Information Science (GIScience 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8728))

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Abstract

This paper defines the Field data type for big spatial data. Most big spatial data sets provide information about properties of reality in continuous way, which leads to their representation as fields. We develop a generic data type for fields that can represent different types of spatiotemporal data, such as trajectories, time series, remote sensing and, climate data. To assess its power of generality, we show how to represent existing algebras for spatial data with the Fields data type. The paper also argues that array databases are the best support for processing big spatial data and shows how to use the Fields data type with array databases.

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Author information

Authors and Affiliations

  1. Image Processing Division, National Institute for Space Research (INPE), São José dos Campos, Brazil

    Gilberto Camara, Karine Ferreira, Pedro Andrade, Gilberto Queiroz & Lubia Vinhas

  2. Institute for Geoinformatics (ifgi), University of Münster, Germany

    Gilberto Camara, Alber Sanchez & Jim Jones

  3. National Center for Geographic Information and Analysis and School of Computing and Information Science, University of Maine, Orono, ME, USA

    Max J. Egenhofer

Authors
  1. Gilberto Camara
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  2. Max J. Egenhofer
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  3. Karine Ferreira
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  4. Pedro Andrade
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  5. Gilberto Queiroz
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  6. Alber Sanchez
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  7. Jim Jones
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  8. Lubia Vinhas
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Editor information

Editors and Affiliations

  1. Department of Infrastructure Engineering, The University of Melbourne, 3010, Victoria, Australia

    Matt Duckham

  2. Institute for Geoinformatics (ifgi), University of Münster, Heisenbergstr. 2, 48149, Münster, Germany

    Edzer Pebesma

  3. Department of Geographical and Sustainability Sciences, The University of Iowa, 305 Jessup Hall, 52242, Iowa City, IA, USA

    Kathleen Stewart

  4. Department for Geodesy and Geoinformation Research Group Geoinformation, Vienna University of Technology, Gusshausstr. 27-29, 1040, Vienna, Austria

    Andrew U. Frank

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© 2014 Springer International Publishing Switzerland

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Camara, G. et al. (2014). Fields as a Generic Data Type for Big Spatial Data. In: Duckham, M., Pebesma, E., Stewart, K., Frank, A.U. (eds) Geographic Information Science. GIScience 2014. Lecture Notes in Computer Science, vol 8728. Springer, Cham. https://doi.org/10.1007/978-3-319-11593-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-11593-1_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11592-4

  • Online ISBN: 978-3-319-11593-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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