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Emergency Information Visualisation

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Abstract

In data-intensive decision making, how to visualize huge, multi-dimension data become an important challenge. In an emergency situation, providing timely information is critical for efficient search and rescue operations. This chapter aims to give an understanding in how information can be designed and presented to give efficient and effective knowledge transfer and decision making. The focus of this chapter is on providing essential comprehension about visualising emergency information. The chapter presents visualisation design objectives and summarises various visualising techniques for content-based, geospatial, and temporal information along with specifics of dashboards. The chapter further introduces some pertinent research issues and finally provides some exercises.

Keywords

  • Emergency information visualisation
  • Design objectives
  • Visualisation techniques
  • Content-based
  • Geospatial
  • Temporal
  • Dashboards

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Notes

  1. 1.

    http://news.mit.edu/2014/in-the-blink-of-an-eye-0116.

  2. 2.

    https://gisgeography.com/gis-formats.

  3. 3.

    http://www.ncgia.ucsb.edu/projects/Cartogram$_$Central/types.html.

  4. 4.

    https://www.gislounge.com/overview-flow-mapping/.

  5. 5.

    http://maxfelsenstein.com/gis-maps/tornado-density-map-1950-2017/.

  6. 6.

    https://revealproject.eu/geoparse-benchmark-open-dataset/.

  7. 7.

    https://d3js.org/d3.v5.js.

  8. 8.

    https://d3js.org/d3.v5.min.js.

  9. 9.

    https://github.com/d3/d3/wiki/Gallery.

  10. 10.

    https://www.d3-graph-gallery.com/graph/wordcloud_size.html.

  11. 11.

    http://bl.ocks.org/NPashaP/a74faf20b492ad377312.

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Acknowledgements

The work is funded from the Research Council of Norway (RCN) and the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education (Diku) grant through INTPART programme.

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Nguyen, H.L., Akerkar, R. (2020). Emergency Information Visualisation. In: Akerkar, R. (eds) Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data. Springer, Cham. https://doi.org/10.1007/978-3-030-48099-8_8

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  • DOI: https://doi.org/10.1007/978-3-030-48099-8_8

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