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Journal ArticleDOI

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

01 Sep 2017-Journal of Flood Risk Management (Newcastle University)-Vol. 10, Iss: 3, pp 370-380
TL;DR: 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.

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Citations
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Journal ArticleDOI
TL;DR: This survey examines the potential and benefits of data-driven research in EWM, gives a synopsis of key concepts and approaches in BigData andML, provides a systematic review of current applications, and discusses major issues and challenges to recommend future research directions.
Abstract: BigData andmachine learning (ML) technologies have the potential to impactmany facets of environment andwatermanagement (EWM). BigData are information assets characterized by high volume, velocity, variety, and veracity. Fast advances in high-resolution remote sensing techniques, smart information and communication technologies, and socialmedia have contributed to the proliferation of BigData inmany EWMfields, such asweather forecasting, disastermanagement, smart water and energymanagement systems, and remote sensing. BigData brings about new opportunities for data-driven discovery in EWM, but it also requires new forms of information processing, storage, retrieval, as well as analytics.ML, a subdomain of artificial intelligence (AI), refers broadly to computer algorithms that can automatically learn fromdata.MLmay help unlock the power of BigData if properly integratedwith data analytics. Recent breakthroughs inAI and computing infrastructure have led to the fast development of powerful deep learning (DL) algorithms that can extract hierarchical features fromdata, with better predictive performance and less human intervention. Collectively BigData andML techniques have shown great potential for data-driven decisionmaking, scientific discovery, and process optimization. These technological advancesmay greatly benefit EWM, especially because (1)many EWMapplications (e.g. early floodwarning) require the capability to extract useful information from a large amount of data in autonomousmanner and in real time, (2)EWMresearches have become highlymultidisciplinary, and handling the ever increasing data volume/types using the traditional workflow is simply not an option, and last but not least, (3) the current theoretical knowledge aboutmany EWMprocesses is still incomplete, but whichmay now be complemented through data-driven discovery. A large number of applications onBigData andML have already appeared in the EWM literature in recent years. The purposes of this survey are to (1) examine the potential and benefits of data-driven research in EWM, (2) give a synopsis of key concepts and approaches in BigData andML, (3) provide a systematic review of current applications, andfinally (4) discussmajor issues and challenges, and recommend future research directions. EWM includes a broad range of research topics. Instead of attempting to survey each individual area, this review focuses on areas of nexus in EWM,with an emphasis on elucidating the potential benefits of increased data availability and predictive analytics to improving the EWMresearch.

210 citations

Journal ArticleDOI
TL;DR: Critical areas for the development of the field include integration of different types of information in data mashups, development of quality assurance procedures and ethical codes, improved integration with existing methods, and assurance of long-term, free and easy-to-access provision of public social media data for future environmental researchers.
Abstract: The analysis of data from social media and social networking sites may be instrumental in achieving a better understanding of human-environment interactions and in shaping future conservation and environmental management. In this study, we systematically map the application of social media data in environmental research. The quantitative review of 169 studies reveals that most studies focus on the analysis of people’s behavior and perceptions of the environment, followed by environmental monitoring and applications in environmental planning and governance. The literature testifies to a very rapid growth in the field, with Twitter (52 studies) and Flickr (34 studies) being most frequently used as data sources. A growing number of studies combine data from multiple sites and jointly investigates multiple types of media. A broader, more qualitative review of the insights provided by the investigated studies suggests that while social media data offer unprecedented opportunities in terms of data volume, scale of analysis, and real-time monitoring, researchers are only starting to cope with the challenges of data’s heterogeneity and noise levels, potential biases, ethics of data acquisition and use, and uncertainty about future data availability. Critical areas for the development of the field include integration of different types of information in data mashups, development of quality assurance procedures and ethical codes, improved integration with existing methods, and assurance of long-term, free and easy-to-access provision of public social media data for future environmental researchers.

203 citations

Book
04 Jul 2016
TL;DR: This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints.
Abstract: Social media is an invaluable source of time-critical information during a crisis. However, emergency response and humanitarian relief organizations that would like to use this information struggle with an avalanche of social media messages that exceeds the human capacity to process. Emergency managers, decision makers, and affected communities can make sense of social media through a combination of machine computation and human compassion - expressed by thousands of digital volunteers who publish, process, and summarize potentially life-saving information. This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints, and offering more than 500 references to in-depth information.

183 citations

Journal ArticleDOI
TL;DR: In this paper, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges.
Abstract: Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity w...

171 citations


Cites background from "Assessing the utility of social med..."

  • ...More recently, Smith et al. (2015) developed a framework for real-time flood mapping using social media data, demonstrating that even a small amount of georeferenced tweets could produce promising results....

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  • ...Social media capture microlevel, real-time information using “citizen-as-sensors” during a flood and have been increasingly utilized for both collecting and disseminating localized information during natural disasters (Smith et al., 2015)....

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Journal ArticleDOI
TL;DR: In this paper, the authors present a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping.
Abstract: Flood events cause substantial damage to urban and rural areas. Monitoring water extent during large-scale flooding is crucial in order to identify the area affected and to evaluate damage. During such events, spatial assessments of floodwater may be derived from satellite or airborne sensing platforms. Meanwhile, an increasing availability of smartphones is leading to documentation of flood events directly by individuals, with information shared in real-time using social media. Topographic data, which can be used to determine where floodwater can accumulate, are now often available from national mapping or governmental repositories. In this work, we present and evaluate a method for rapidly estimating flood inundation extent based on a model that fuses remote sensing, social media and topographic data sources. Using geotagged photographs sourced from social media, optical remote sensing and high-resolution terrain mapping, we develop a Bayesian statistical model to estimate the probability of flood inundation through weights-of-evidence analysis. Our experiments were conducted using data collected during the 2014 UK flood event and focus on the Oxford city and surrounding areas. Using the proposed technique, predictions of inundation were evaluated against ground-truth flood extent. The results report on the quantitative accuracy of the multisource mapping process, which obtained area under receiver operating curve values of 0.95 and 0.93 for model fitting and testing, respectively.

171 citations


Cites background from "Assessing the utility of social med..."

  • ...On the other side, various crowdsourcing data (e.g. Flickr, citizen science, Twitter) come with less controlled quality assurance, but are timely....

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  • ...Although the experiments here exploit geotagged images sourced from social media, the rapid inundation mapping methodology employed could incorporate other crowdsourced assessments such as Twitter (Panteras et al. 2014; Smith et al. 2015) or volunteered by citizens (Poser et al. 2009)....

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  • ...Although the experiments here exploit geotagged images sourced from social media, the rapid inundation mapping methodology employed could incorporate other crowdsourced assessments such as Twitter (Panteras et al. 2014; Smith et al. 2015) or volunteered by citizens (Poser et al....

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References
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Book
04 Sep 2011
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.
Abstract: Problems involving the classical linear partial differential equations of mathematical physics can be reduced to algebraic ones of a very much simpler structure by replacing the differentials by difference quotients on some (say rectilinear) mesh. This paper will undertake an elementary discussion of these algebraic problems, in particular of the behavior of the solution as the mesh width tends to zero. For present purposes we limit ourselves mainly to simple but typical cases, and treat them in such a way that the applicability of the method to more general difference equations and to those with arbitrarily many independent variables is made clear.

2,047 citations


"Assessing the utility of social med..." refers methods in this paper

  • ...Consequently, the explicit models are constrained by the Courant–Friedrichs–Lewy condition (Courant et al., 1967), which is a function of the largest velocity within the domain and the cell dimensions; accordingly, if the cell resolution of these models is halved, the simulation run-time can be expected to increase by approximately eight times....

    [...]

  • ...Consequently, the explicit models are constrained by the Courant-Friedrichs-Lewy condition (Courant et al., 1967), which is a function of the largest velocity within the domain and the cell dimensions; accordingly, if the cell resolution of these models is halved, the simulation run-time can be…...

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Proceedings ArticleDOI
10 Apr 2010
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.
Abstract: We analyze microblog posts generated during two recent, concurrent emergency events in North America via Twitter, a popular microblogging service. We focus on communications broadcast by people who were "on the ground" during the Oklahoma Grassfires of April 2009 and the Red River Floods that occurred in March and April 2009, and identify information that may contribute to enhancing situational awareness (SA). This work aims to inform next steps for extracting useful, relevant information during emergencies using information extraction (IE) techniques.

1,479 citations


"Assessing the utility of social med..." refers background in this paper

  • ...…and communication during times of crisis and natural disasters, such as during the 2011 Queensland flood and Thai flood (Starbird et al., 2010; Vieweg et al., 2010; Kongthon et al., 2012; Murthy and Longwell, 2012); the accuracy and validity of information provided by the public through…...

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Proceedings ArticleDOI
06 Feb 2010
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.
Abstract: This paper considers a subset of the computer-mediated communication (CMC) 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, we identified mechanisms of information production, distribution, and organization. The Red River event resulted in a rapid generation of Twitter communications by numerous sources using a variety of communications forms, including autobiographical and mainstream media reporting, among other types. We examine the social life of microblogged information, identifying generative, synthetic, derivative and innovative properties that sustain the broader system of interaction. The landscape of Twitter is such that the production of new information is supported through derivative activities of directing, relaying, synthesizing, and redistributing, and is additionally complemented by socio-technical innovation. These activities comprise self-organization of information.

493 citations


"Assessing the utility of social med..." refers background in this paper

  • ...…as a tool for dissemination and communication during times of crisis and natural disasters, such as during the 2011 Queensland flood and Thai flood (Starbird et al., 2010; Vieweg et al., 2010; Kongthon et al., 2012; Murthy and Longwell, 2012); the accuracy and validity of information provided by…...

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  • ...Clear evidence exists that social media is increasingly used as a tool for dissemination and communication during times of crisis and natural disasters, such as during the 2011 Queensland flood and Thai flood (Starbird et al., 2010; Vieweg et al., 2010; Kongthon et al., 2012; Murthy and Longwell, 2012); the accuracy and validity of information provided by the public through social media such as Twitter however may be questionable....

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Journal ArticleDOI
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.
Abstract: In just under seven years, Twitter has grown to count nearly 3% of the entire global population among its active users who have sent more than 170 billion 140-character messages. Today the service plays such a significant role in American culture that the Library of Congress has assembled a permanent archive of the site back to its first tweet, updated daily. With its open API, Twitter has become one of the most popular data sources for social research, yet the majority of the literature has focused on it as a text or network graph source, with only limited efforts to date focusing exclusively on the geography of Twitter, assessing the various sources of geographic information on the service and their accuracy. More than 3% of all tweets are found to have native location information available, while a naive geocoder based on a simple major cities gazetteer and relying on the user-provided Location and Profile fields is able to geolocate more than a third of all tweets with high accuracy when measured against the GPS-based baseline. 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.

391 citations


"Assessing the utility of social med..." refers background in this paper

  • ...Comparison of locations geocoded from the text within Tweets against the actual location of the user from geotags suggests even when Tweets are geotagged, this data can rarely be considered reliable for inferring flooded locations (Leetaru et al., 2013)....

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  • ...reliable for inferring flooded locations (Leetaru et al., 2013)....

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Journal ArticleDOI
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.

291 citations


"Assessing the utility of social med..." refers background in this paper

  • ...Steep slopes and narrow gaps can induce supercritical flow conditions, resulting in such phenomena as hydraulic jumps, and thus requiring shock-capturing but computationally intensive models if they are to be accurately reproduced (Mignot et al., 2006)....

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  • ...gaps can induce supercritical flow conditions, resulting in such phenomena as hydraulic jumps, and thus requiring shock-capturing but computationally intensive models if they are to be accurately reproduced (Mignot et al., 2006)....

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