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An analytics dashboard visualization for flood decision support system

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Abstract

Nowadays, visual analytics dashboard for decision support system for disaster management is very essential, as the frequency of several disasters is growing rapidly. It is very useful to take decision in time-sensitive environment from diverse rapid data set. Thus, it is critical to reduce the overhead in data integration and visualization for efficient decision making. Geographical map visualization can be an effective solution in such environments by providing an integrated approach to extract, integrate, and view diverse information. In this paper, an analytics dashboard has been developed for identifying and visualizing risk zones and vulnerable areas before disaster has occurred. For this, rescuer will have more time to be prepared and a better plan will be produced to rescue the people and reallocate them into safe areas.

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Acknowledgements

We would like to thank Prof. K. Koyamada and Prof. K. C. Kim, Editor-in-Chief of Journal of Visualization for being supportive towards the publication of this paper. Special thanks are due to the two anonymous reviewers whose comments greatly improved the presentation. Thanks are due to the Indian Statistical Institute Kolkata, India for funding this study. We are also thankful to the government personnel of Irrigation & Waterways Department of West Bengal and India Meteorological Department for their cooperation and help.

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Authors and Affiliations

  1. Statistical Quality Control and Operations Research Unit, Indian Statistical Institute, No. 203, Barrackpore Trunk Road, Kolkata, West Bengal, 700108, India

    Sudipto Saha, Shashank Shekhar, Sounak Sadhukhan & Prasun Das

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  1. Sudipto Saha
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  2. Shashank Shekhar
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  3. Sounak Sadhukhan
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  4. Prasun Das
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Correspondence to Sounak Sadhukhan.

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Saha, S., Shekhar, S., Sadhukhan, S. et al. An analytics dashboard visualization for flood decision support system. J Vis 21, 295–307 (2018). https://doi.org/10.1007/s12650-017-0453-3

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  • DOI: https://doi.org/10.1007/s12650-017-0453-3

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