Articles | Volume 15, issue 12
Nat. Hazards Earth Syst. Sci., 15, 2725–2738, 2015
https://doi.org/10.5194/nhess-15-2725-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Natural hazard event analyses for risk reduction and...
Research article
21 Dec 2015
Research article
| 21 Dec 2015
Social media as an information source for rapid flood inundation mapping
J. Fohringer et al.
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111 citations as recorded by crossref.
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- Direct local building inundation depth determination in 3-D point clouds generated from user-generated flood images L. Griesbaum et al. 10.5194/nhess-17-1191-2017
- Using crowdsourced web content for informing water systems operations in snow-dominated catchments M. Giuliani et al. 10.5194/hess-20-5049-2016
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- Modeling of contaminant transport during an urban pluvial flood event – The importance of surface flow R. Sämann et al. 10.1016/j.jhydrol.2018.10.002
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- Urban flood modelling combining cellular automata framework with semi-implicit finite difference numerical formulation U. Nkwunonwo et al. 10.1016/j.jafrearsci.2018.10.016
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- Low-Cost Solution for Assessment of Urban Flash Flood Impacts Using Sentinel-2 Satellite Images and Fuzzy Analytic Hierarchy Process: A Case Study of Ras Ghareb City, Egypt M. Sadek & X. Li 10.1155/2019/2561215
- Stochastic Modeling for Estimating Real-Time Inundation Depths at Roadside IoT Sensors Using the ANN-Derived Model S. Wu et al. 10.3390/w13213128
- Exploring the influence of citizen involvement on the assimilation of crowdsourced observations: a modelling study based on the 2013 flood event in the Bacchiglione catchment (Italy) M. Mazzoleni et al. 10.5194/hess-22-391-2018
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- Event relatedness assessment of Twitter messages for emergency response F. Laylavi et al. 10.1016/j.ipm.2016.09.002
- Automatic Estimation of Urban Waterlogging Depths from Video Images Based on Ubiquitous Reference Objects J. Jiang et al. 10.3390/rs11050587
- Potential and Limitations of Open Satellite Data for Flood Mapping D. Notti et al. 10.3390/rs10111673
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- Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne, Germany K. Tzavella et al. 10.1007/s11069-017-3102-1
- Rapid flood inundation mapping by differencing water indices from pre- and post-flood Landsat images R. Sivanpillai et al. 10.1007/s11707-020-0818-0
- Flood Forecasting System Based on Integrated Big and Crowdsource Data by Using Machine Learning Techniques S. Puttinaovarat & P. Horkaew 10.1109/ACCESS.2019.2963819
- Invited perspectives: How machine learning will change flood risk and impact assessment D. Wagenaar et al. 10.5194/nhess-20-1149-2020
- Social Media: New Perspectives to Improve Remote Sensing for Emergency Response J. Li et al. 10.1109/JPROC.2017.2684460
- Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. 10.1002/wat2.1520
- Free Global DEMs and Flood Modelling—A Comparison Analysis for the January 2015 Flooding Event in Mocuba City (Mozambique) J. Garrote 10.3390/w14020176
- How to improve attribution of changes in drought and flood impacts H. Kreibich et al. 10.1080/02626667.2018.1558367
- DisKnow: A Social-Driven Disaster Support Knowledge Extraction System J. Boné et al. 10.3390/app10176083
- Emergency flood detection using multiple information sources: Integrated analysis of natural hazard monitoring and social media data K. Shoyama et al. 10.1016/j.scitotenv.2020.144371
- Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community J. Ball et al. 10.1117/1.JRS.11.042609
- Demonstrating the value of community-based (‘citizen science’) observations for catchment modelling and characterisation E. Starkey et al. 10.1016/j.jhydrol.2017.03.019
- Detecting flood inundation information through Twitter: The 2015 Kinu River flood disaster in Japan Y. Shi et al. 10.2328/jnds.40.1
- Preface: Damage of natural hazards: assessment and mitigation H. Kreibich et al. 10.5194/nhess-19-551-2019
- Damage classification and recovery analysis of the Chongqing, China, floods of August 2020 based on social-media data L. Tan & D. Schultz 10.1016/j.jclepro.2021.127882
- Measuring the Impact of Natural Hazards with Citizen Science: The Case of Flooded Area Estimation Using Twitter P. Bruneau et al. 10.3390/rs13061153
- The Missing Parts from Social Media–Enabled Smart Cities: Who, Where, When, and What? Y. Yuan et al. 10.1080/24694452.2019.1631144
- Situational awareness extraction: a comprehensive review of social media data classification during natural hazards J. Vongkusolkit & Q. Huang 10.1080/19475683.2020.1817146
- Social media data crowdsourcing as a new stream for environmental planning & monitoring: A review B. Lawu et al. 10.1088/1755-1315/729/1/012013
- Citizen observations contributing to flood modelling: opportunities and challenges T. Assumpção et al. 10.5194/hess-22-1473-2018
- Water level prediction from social media images with a multi-task ranking approach P. Chaudhary et al. 10.1016/j.isprsjprs.2020.07.003
- Social Media Use in Emergency Response to Natural Disasters: A Systematic Review With a Public Health Perspective K. Muniz-Rodriguez et al. 10.1017/dmp.2020.3
- Opportunities and risks of disaster data from social media: a systematic review of incident information M. Wiegmann et al. 10.5194/nhess-21-1431-2021
- Urban surface water flood modelling – a comprehensive review of current models and future challenges K. Guo et al. 10.5194/hess-25-2843-2021
- Hyper-resolution monitoring of urban flooding with social media and crowdsourcing data R. Wang et al. 10.1016/j.cageo.2017.11.008
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- Temporal and Spatial Evolution and Influencing Factors of Public Sentiment in Natural Disasters—A Case Study of Typhoon Haiyan T. Zhang & C. Cheng 10.3390/ijgi10050299
- Flood hazard assessment and the role of citizen science B. Sy et al. 10.1111/jfr3.12519
- Utilizing Geo-Social Media as a Proxy Data for Enhanced Flood Monitoring J. Sattaru et al. 10.1007/s12524-021-01376-9
- Spatial exposure aspects contributing to vulnerability and resilience assessments of urban critical infrastructure in a flood and blackout context A. Fekete et al. 10.1007/s11069-016-2720-3
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Short summary
During and shortly after a disaster, data about the hazard and its consequences are scarce and not readily available. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in the case of floods. The case study of the June 2013 flood in the city of Dresden shows that social media may help to bridge the information gap when traditional data sources are lacking or are sparse.
During and shortly after a disaster, data about the hazard and its consequences are scarce and...
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