Articles | Volume 17, issue 5
https://doi.org/10.5194/nhess-17-735-2017
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, Dirk Eilander, Arnejan van Loenen, Martijn J. Booij, Kathelijne M. Wijnberg, Jan S. Verkade, and Jurjen Wagemaker

Data sets

Twitter Flood Mapping Scripts: First Release T. Brouwer https://doi.org/10.5281/zenodo.165818

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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.
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