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Detecting Collapsed Buildings in Case of Disaster: Which Visualisation Works Best?
Department of Geography, Ghent University, Ghent, Belgium.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.ORCID iD: 0000-0002-5986-7464
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.ORCID iD: 0000-0003-0085-5829
2018 (English)In: Eye Tracking for Spatial Research: Proceedings of the 3rd International Workshop / [ed] Kiefer, Peter Giannopoulos, Ioannis Göbel, Fabian Raubal, Martin Duchowski, Andrew T., Zurich, 2018Conference paper, Published paper (Refereed)
Abstract [en]

A user study is conducted to evaluate the efficiency and effectiveness of two types of visualizations to identify damage sites in case of disaster. The test consists out 36 trials (18 for each visualisation) and in each trial an area of 1x1km, located in Ghent, is displayed on a screen. This image shows the combined height information from before and after the disaster. The first visualisation, page flipping, is based on greyscale images with height information from the pre- and post-disaster situation between which users can switch manually. The second visualisation, difference image, is a result of subtracting the heights (before versus after) and assigning a blue-white-red colour ramp. In order to simulate the urgency with which the data is captured, systematic and random imperfections are introduced in the post-disaster data. All participants’ mouse and key interactions are logged, which is further complemented by the registration of their eye movements. This give insights the visualizations’ efficiency, effectiveness and the overall search strategies of the participants.

Place, publisher, year, edition, pages
Zurich, 2018.
Keywords [en]
user study; mouse & key logging; eye tracking; emergency response; damage assessment
National Category
Computer Systems
Research subject
Sustainable Urban Development
Identifiers
URN: urn:nbn:se:hig:diva-29175DOI: 10.3929/ethz-b-000222480OAI: oai:DiVA.org:hig-29175DiVA, id: diva2:1282716
Conference
3rd International Workshop on Eye Tracking for Spatial Research, January 14, 2018, Zurich, Switzerland
Available from: 2019-01-25 Created: 2019-01-25 Last updated: 2025-10-02Bibliographically approved

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Åhlén, JuliaSeipel, Stefan

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CiteExportLink to record
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Citation style
  • apa
  • harvard-cite-them-right
  • ieee
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Language
  • sv-SE
  • en-GB
  • en-US
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  • nn-NB
  • de-DE
  • Other locale
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Output format
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