Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework
TLDR
In this paper, a real-time modelling framework is presented to identify areas likely to have flooded using data obtained only through social media, using graphics processing unit (GPU) accelerated hydrodynamic modelling.Abstract:
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.read more
Citations
More filters
Journal ArticleDOI
Assessment of crowdsourced social media data and numerical modelling as complementary tools for urban flood mitigation
TL;DR: In this article , the authors explored how crowdsourced social media data complemented urban flood modelling to improve model performance and achieve a better classification of impacts, and the complementation of crowdsourced data and urban modelling enhances the understanding of the flood dynamics, thus offering a framework for the generation of flood risk management products.
Journal ArticleDOI
Rapid urban flood risk mapping for data-scarce environments using social sensing and region-stable deep neural network
TL;DR: Wang et al. as mentioned in this paper presented an alternative near real-time flood risk mapping method for data scarce environments developed using social sensing and region-stable deep neural network (RS-DNN).
Exploring the utility of social media data for urban flood impact assessment in data scarce cities
TL;DR: Wang et al. as discussed by the authors developed a workflow framework to assess urban flood impacts by extracting and analysing social media data, as well as identifying the intensive public response areas, using the case of 2020 China Chengdu rainstorm-induced flooding.
Journal ArticleDOI
Comparison of deep-water-parameter-based wave overtopping with wirewall field measurements and social media reports at Crosby (UK)
TL;DR: In this article , the authors validate a set of deep-water-parameter-based formulae for mean overtopping discharge (q) at smooth slopes, which remove the need for nearshore measurements or additional numerical modelling but require that a single representative foreshore slope angle (m) be defined.
Proceedings ArticleDOI
Quality assessment in Volunteered Geographic Information for Risk Management applications
TL;DR: The review of a number of case studies in the literature illustrates the pertinence of the use of geo-referenced crowd sourced data to improve the efficiency of risk management approaches particularly in poor mapped area or/and where real-time and up-to-date data is needed.
References
More filters
Book
On the partial difference equations of mathematical physics
TL;DR: In this paper, a discussion of the behavior of the solution as the mesh width tends to zero is presented, and the applicability of the method to more general difference equations and to those with arbitrarily many independent variables is made clear.
Proceedings ArticleDOI
Microblogging during two natural hazards events: what twitter may contribute to situational awareness
TL;DR: Analysis of microblog posts generated during two recent, concurrent emergency events in North America via Twitter, a popular microblogging service, aims to inform next steps for extracting useful, relevant information during emergencies using information extraction (IE) techniques.
Proceedings ArticleDOI
Chatter on the red: what hazards threat reveals about the social life of microblogged information
TL;DR: This paper considers a subset of the computer-mediated communication that took place during the flooding of the Red River Valley in the US and Canada in March and April 2009, focusing on the use of Twitter, a microblogging service, to identify mechanisms of information production, distribution, and organization.
Journal ArticleDOI
Mapping the global Twitter heartbeat: The geography of Twitter
TL;DR: Geographic proximity is found to play a minimal role both in who users communicate with and what they communicate about, providing evidence that social media is shifting the communicative landscape.
Journal ArticleDOI
Modeling floods in a dense urban area using 2D shallow water equations
TL;DR: In this article, a code solving the 2D shallow water equations by an explicit second-order scheme is used to simulate the severe October 1988 flood in the Richelieu urban locality of the French city of Nimes.