Predicting floods with Flickr tags

Tkachenko, Nataliya; Jarvis, Stephen A.; Procter, Rob

doi:10.1371/journal.pone.0172870

Cited by 44 publications

(36 citation statements)

References 18 publications

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“…As reported by Esposito et al [61], many studies have underlined the valuable use of web news and social media for flood mapping [62], streamflow estimation [63,64], damage assessment [65], and flood prediction [66,67]. Crowdsourced data and Volunteered Geographic Information (VGI) have also been used to develop road damage maps, representing a fundamental tool in disaster response operations [68].…”

Section: Evaluation Of Flooding Impact Using Crowdsourced Datamentioning

confidence: 99%

Characterizing Consecutive Flooding Events after the 2017 Mt. Salto Wildfires (Southern Italy): Hazard and Emergency Management Implications

Esposito¹,

Parodi²,

Lagasio³

et al. 2019

Water

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Every summer, wildfires affect thousands of steep watersheds in Italy, causing the partial or complete destruction of vegetation, and changes in soil hydraulic properties. Such effects alter the hydrologic response of watersheds, increasing post-fire debris and sediment-laden flow hazard. This study characterizes the most relevant predisposing and triggering factors for a sequence of four post-fire flooding events, which, in the late summer-autumn of 2017, affected Montoro village in southern Italy. This research work consists of a fire severity assessment based on multispectral satellite images, characterization of meteorological systems and related flood-triggering rainfall, and provides an overview of the damage that occurred in the repeatedly affected urban area using crowdsourced data. The research findings demonstrate that the analyzed area burned with moderate-high (64.4%) and low severity (35.6%) levels. All the flooding events were triggered by rainfall evaluated as non-extreme, but with relevant peak intensities (I10 and I30), associated with the first convective storms impacting the burned watersheds. The crowdsourced data highlight the fact that roads and buildings on footslopes were inundated by mud and debris transported by rapid flows. The study identifies a clear relationship between wildfires and flooding processes and provides useful information for hazard assessment and emergency management operations.

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Section: Evaluation Of Flooding Impact Using Crowdsourced Datamentioning

confidence: 99%

Characterizing Consecutive Flooding Events after the 2017 Mt. Salto Wildfires (Southern Italy): Hazard and Emergency Management Implications

Esposito¹,

Parodi²,

Lagasio³

et al. 2019

Water

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show abstract

“…There are several initiatives including projects and applications that exploit social media, such as Flickr tags [20], in order to create awareness about emergency situations or any other health related issues such as environmental conditions. First, within the hackAIR project [12], a platform has been developed for gathering and fusing environmental data and specifically Particulate Matter measurements from official sources and social media communities such as publicly available images shared through Instagram.…”

Section: Related Workmentioning

confidence: 99%

Flood Relevance Estimation from Visual and Textual Content in Social Media Streams

Moumtzidou

Andreadis

Gialampoukidis

et al. 2018

Companion of the the Web Conference 2018 on the Web Conference 2018 - WWW '18

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Disaster monitoring based on social media posts has raised a lot of interest in the domain of computer science the last decade, mainly due to the wide area of applications in public safety and security and due to the pervasiveness not solely on daily communication but also in life-threating situations. Social media can be used as a valuable source for producing early warnings of eminent disasters. This paper presents a framework to analyse social media multimodal content, in order to decide if the content is relevant to flooding. This is very important since it enhances the crisis situational awareness and supports various crisis management procedures such as preparedness. Evaluation on a benchmark dataset shows very good performance in both text and image classification modules.

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“…In addition, social media data have proved to be capable of revealing the disaster-affected population [9]. First, data derived from social media have been shown to have strong relationships with the extent of damage from natural disasters [10][11][12][13]. Second, combined with other disaster-related data, such as geographical information and remote sensing images, social media data can enhance and improve useful information extracted for emergency response [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

Cheng

Zhang

et al. 2019

IJGI

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Complex natural disasters often cause people to suffer hardships, and they can cause a large number of casualties. A population that has been affected by a natural disaster is at high risk and desperately in need of help. Even with the timely assessment and knowledge of the degree that natural disasters affect populations, challenges arise during emergency response in the aftermath of a natural disaster. This paper proposes an approach to assessing the near-real-time intensity of the affected population using social media data. Because of its fatal impact on the Philippines, Typhoon Haiyan was selected as a case study. The results show that the normalized affected population index (NAPI) has a significant ability to indicate the affected population intensity. With the geographic information of disasters, more accurate and relevant disaster relief information can be extracted from social media data. The method proposed in this paper will benefit disaster relief operations and decision-making, which can be executed in a timely manner.

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Predicting floods with Flickr tags

Cited by 44 publications

References 18 publications

Characterizing Consecutive Flooding Events after the 2017 Mt. Salto Wildfires (Southern Italy): Hazard and Emergency Management Implications

Characterizing Consecutive Flooding Events after the 2017 Mt. Salto Wildfires (Southern Italy): Hazard and Emergency Management Implications

Flood Relevance Estimation from Visual and Textual Content in Social Media Streams

Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

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