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Perceivability of Map Information for Disaster Situations for People with Low Vision

  • Siv Tunold
  • Jaziar Radianti
  • Terje GjøsæterEmail author
  • Weiqin Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11572)

Abstract

Digital maps have become increasingly popular in disaster situation to provide overview of information. However, these maps have also created barriers for many people, particularly people with visual impairments. Existing research on accessible maps such as tactile and acoustic maps focuses on providing solutions for blind persons to be able to perceive the information digital maps present. For people with low vision, who often rely on magnifier, good contrast and good navigation support, current digital map solutions present many challenges. In this paper we have studied two types of digital maps and their related surrounding text in the home page of disaster applications. The study focused on perceivability of the information provided by the maps. To investigate this, we have adopted a mix-method approach and performed heuristic testing combined with expert testing by a user with low vision. Based on the evaluation we have made a number of recommendations to improve the perceivability, which can further enhance the accessibility of the maps.

Keywords

Maps Universal design Perceivability Emergency management Low vision 

References

  1. 1.
    Huang, H., et al.: Web3DGIS-based system for reservoir landslide monitoring and early warning. Appl. Sci. 6(2), 44 (2016)CrossRefGoogle Scholar
  2. 2.
    Clarke, A.E., Friese, C., Washburn, R.: Situational Analysis in Practice: Mapping Research with Grounded Theory. Routledge, Abingdon (2016)CrossRefGoogle Scholar
  3. 3.
    Yamamoto, K., Li, X.: Safety evaluation of evacuation routes in Central Tokyo assuming a large-scale evacuation in case of earthquake disasters. J. Risk Financ. Manag. 10(3), 14 (2017)CrossRefGoogle Scholar
  4. 4.
    Doeweling, S., et al.: Support for collaborative situation analysis and planning in crisis management teams using interactive tabletops. In: Proceedings of the 2013 ACM International Conference on Interactive Tabletops and Surfaces. ACM (2013)Google Scholar
  5. 5.
    Ganz, A., et al.: Urban search and rescue situational awareness using DIORAMA disaster management system. Procedia Eng. 107, 349–356 (2015)CrossRefGoogle Scholar
  6. 6.
    Chen, A.Y., Peña-Mora, F., Ouyang, Y.: A collaborative GIS framework to support equipment distribution for civil engineering disaster response operations. Autom. Constr. 20(5), 637–648 (2011)CrossRefGoogle Scholar
  7. 7.
    Miura, H., Midorikawa, S., Matsuoka, M.: Building damage assessment using high-resolution satellite SAR images of the 2010 Haiti earthquake. Earthq. Spectra 32(1), 591–610 (2016)CrossRefGoogle Scholar
  8. 8.
    Giardino, M., et al.: GIS and geomatics for disaster management and emergency relief: a proactive response to natural hazards. Appl. Geomat. 4(1), 33–46 (2012)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Freire, S.: Modeling of spatiotemporal distribution of urban population at high resolution – value for risk assessment and emergency management. In: Konecny, M., Zlatanova, S., Bandrova, T. (eds.) Geographic Information and Cartography for Risk and Crisis Management. Lecture Notes in Geoinformation and Cartography, pp. 53–67. Springer, Berlin (2010).  https://doi.org/10.1007/978-3-642-03442-8_4CrossRefGoogle Scholar
  10. 10.
    Radianti, J., Gjøsæter, T.: Digital volunteers in disaster response: accessibility challenges. In: HCII 2019. Springer, Orlando (2019, in press)Google Scholar
  11. 11.
    Cardonha, C., et al.: A crowdsourcing platform for the construction of accessibility maps. In: Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility. ACM (2013)Google Scholar
  12. 12.
    Gjøsæter, T., Radianti, J., Chen, W.: Universal design of ICT for emergency management. In: Antona, M., Stephanidis, C. (eds.) UAHCI 2018. LNCS, vol. 10907, pp. 63–74. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-92049-8_5CrossRefGoogle Scholar
  13. 13.
    Klaus, H., et al.: AccessibleMap. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  14. 14.
    Zeng, L., Weber, G.: ATMap: annotated tactile maps for the visually impaired. In: Esposito, A., Esposito, Antonietta M., Vinciarelli, A., Hoffmann, R., Müller, Vincent C. (eds.) Cognitive Behavioural Systems. LNCS, vol. 7403, pp. 290–298. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-34584-5_25CrossRefGoogle Scholar
  15. 15.
    Szpiro, S.F.A., et al.: How people with low vision access computing devices: understanding challenges and opportunities. In: Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility, pp. 171–180. ACM, Reno (2016)Google Scholar
  16. 16.
    Boccardo, P.: New perspectives in emergency mapping. Eur. J. Remote Sens. 46(1), 571–582 (2013)CrossRefGoogle Scholar
  17. 17.
    Wang, Z., et al.: Instant tactile-audio map: enabling access to digital maps for people with visual impairment. In: Proceedings of the 11th International ACM SIGACCESS Conference on Computers and Accessibility. ACM (2009)Google Scholar
  18. 18.
    Fernandes, H., et al.: Providing accessibility to blind people using GIS. Univers. Access Inf. Soc. 11(4), 399–407 (2012)CrossRefGoogle Scholar
  19. 19.
    WHO: ICD-11 for Mortality and Morbidity Statistics. 9D90 Vision Impairment Including Blindness. WHO (2018)Google Scholar
  20. 20.
    Maptimize: #onemilliontweetmap (2017). http://www.onemilliontweetmap.com/
  21. 21.
  22. 22.
    WAI: W.A.I. Easy Checks - A First Review of Web Accessibility (2019). http://www.w3.org/WAI/test-evaluate/preliminary/

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Oslo Metropolitan UniversityOsloNorway
  2. 2.CIEMUniversity of AgderGrimstadNorway

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