Natural Hazards

, Volume 93, Issue 3, pp 1529–1546 | Cite as

Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study

  • Faxi Yuan
  • Rui Liu
Original Paper


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.


Crowdsourcing Crowdsensor Forensic disaster investigations Data-driven Scenario Hurricane Harvey 

Supplementary material

11069_2018_3366_MOESM1_ESM.csv (400 kb)
Supplementary material 1 (CSV 400 kb)
11069_2018_3366_MOESM2_ESM.xlsx (92 kb)
Supplementary material 2 (XLSX 91 kb)


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.M.E. Rinker, Sr. School of Construction ManagementUniversity of FloridaGainesvilleUSA

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