Assessing the utility of social media as a data source for flood risk management using a real‐time modelling framework

By Luke Smith, Qiuhua Liang, Philip James, Wen Lin. 2017

251 citations recorded by the source corpus.

The utility of social media for both collecting and disseminating information during natural disasters is increasingly recognised. The rapid nature of urban flooding from intense rainfall means accurate surveying of peak depths and flood extents is rarely achievable, hindering the validation of urban flood models. This paper presents a real‐time modelling framework to identify areas likely to have flooded using data obtained only through social media. Graphics processing unit (GPU) accelerated hydrodynamic modelling is used to simulate flooding in a 48‐km2 area of Newcastle upon Tyne, with results automatically compared against flooding identified through social media, allowing inundation to be inferred elsewhere in the city with increased detail and accuracy. Data from Twitter during two 2012 flood events are used to test the framework, with the inundation results indicative of good agreement against crowd‐sourced and anecdotal data, even though the sample of successfully geocoded Tweets was relatively small.

Subfields: Atmospheric Science, Communication, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a56bcac981f91e0ab96ec1f9c1119df5b0a897d8

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In Atmospheric Science

1. Michael Sinclair
2. Andrea Ghermandi

In Communication

1. Michael Sinclair
2. Andrea Ghermandi

In Global and Planetary Change

1. Michael Sinclair
2. Andrea Ghermandi

Citations in the corpus

• Passive crowdsourcing of social media in environmental research: A systematic map (2019, methodology): “…al., 2015), tweets (Riga et al., 2015) and blogs (Wang et al., 2017b; Ni et al., 2017); and mapping of flooding levels through analysis of tweets (Smith et al., 2017; Jongman et al., 2015; Fohringer et al., 2015), Flickr photos (Tkachenko et al., 2017; Sun et al., 2016; Fohringer et al., 2015)…”