Articles | Volume 17, issue 5
Nat. Hazards Earth Syst. Sci., 17, 735–747, 2017
https://doi.org/10.5194/nhess-17-735-2017
Nat. Hazards Earth Syst. Sci., 17, 735–747, 2017
https://doi.org/10.5194/nhess-17-735-2017

Research article 19 May 2017

Research article | 19 May 2017

Probabilistic flood extent estimates from social media flood observations

Tom Brouwer et al.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by Editor and Referees) (06 Mar 2017) by Paolo Tarolli
AR by Dirk Eilander on behalf of the Authors (08 Mar 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (14 Mar 2017) by Paolo Tarolli
RR by Anonymous Referee #1 (24 Mar 2017)
RR by Anonymous Referee #2 (29 Mar 2017)
ED: Publish subject to technical corrections (18 Apr 2017) by Paolo Tarolli
AR by Tom Brouwer on behalf of the Authors (25 Apr 2017)  Author's response    Manuscript
Download
Short summary
The increasing number and severity of floods, driven by e.g. urbanization, subsidence and climate change, create a growing need for accurate and timely flood maps. At the same time social media is a source of much real-time data that is still largely untapped in flood disaster management. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.
Altmetrics
Final-revised paper
Preprint