Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study

Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study A critical prerequisite of risk prevention measures for natural hazards is from the results of forensic disaster investigations (FDIs). The current studies of the FDIs are limited by data issues including data availability and data reliability. The applications of crowdsourcing method in natural disasters indicate the potential to provide data support for the FDIs. However, there is very limited existing research on the use of crowdsourcing data for the FDIs. Following the requirements published by the Integrated Research on Disaster Risk program for FDIs, this paper establishes the process map for conducting the FDIs by scenario analysis approach with the crowdsourcing and crowdsensor data. Hurricane Harvey is used as the case study to implement the process map. The results show that the use of crowdsourcing data for the FDIs is feasible. Though this paper takes practical measures for improving the reliability of crowdsourcing data (i.e., little data size) in the case study, future research can focus on the development of advanced algorithm for the crowdsourcing data quality validation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Natural Hazards Springer Journals

Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Earth Sciences; Natural Hazards; Hydrogeology; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Civil Engineering; Environmental Management
ISSN
0921-030X
eISSN
1573-0840
D.O.I.
10.1007/s11069-018-3366-0
Publisher site
See Article on Publisher Site

Abstract

A critical prerequisite of risk prevention measures for natural hazards is from the results of forensic disaster investigations (FDIs). The current studies of the FDIs are limited by data issues including data availability and data reliability. The applications of crowdsourcing method in natural disasters indicate the potential to provide data support for the FDIs. However, there is very limited existing research on the use of crowdsourcing data for the FDIs. Following the requirements published by the Integrated Research on Disaster Risk program for FDIs, this paper establishes the process map for conducting the FDIs by scenario analysis approach with the crowdsourcing and crowdsensor data. Hurricane Harvey is used as the case study to implement the process map. The results show that the use of crowdsourcing data for the FDIs is feasible. Though this paper takes practical measures for improving the reliability of crowdsourcing data (i.e., little data size) in the case study, future research can focus on the development of advanced algorithm for the crowdsourcing data quality validation.

Journal

Natural HazardsSpringer Journals

Published: Jun 4, 2018

References

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