Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review

Arshad, Bilal; Ogie, Robert Ighodaro; Barthélemy, Johan; Pradhan, Biswajeet; Verstaevel, Nicolas; Perez, Pascal

doi:10.3390/s19225012

Cited by 90 publications

(53 citation statements)

References 117 publications

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“…From this point of view, the use of a single application would optimise and accelerate response management (Park, 2017 ; Verrucci et al, 2016 ) and could strengthen local capacities among regions for disaster preparedness. Moreover, using artificial neural networks (Pashazadeh & Javan, 2020 ) and artificial intelligence (Abarca-Alvarez et al, 2019 ) for building forecasting models (Ogania et al, 2019 ; Williams & Lück-Vogel, 2020 ) could have a beneficial impact, and it could be adequately complemented by spatial–temporal detection systems (Yu et al, 2020 ) and the Internet of Things (Arshad et al, 2019 ; Xu et al, 2018 ).…”

Section: Resultsmentioning

confidence: 99%

“…Other ICTs that are proving to be relevant to all phases of DRM are the development of geographical information systems (GIS) (Hongbo et al, 2014 ) and remote sensing (Sausen & Lacruz, 2015 ; Troy et al, 2008 ). It is also interesting to consider the contributions of the Internet of Things applied to evacuation plans (Xu et al, 2018 ), early warning systems, and risk monitoring (Arshad et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the adequacy of mobile applications for disaster reduction

Corcuera

Barbero–Barrera

Hidalgo

et al. 2021

Environ Dev Sustain

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Natural events continue to take a heavy toll on human lives. Added to this are the challenge of dynamic at-risk settings, uncertainty, and increasing threats, which demand holistic, flexible, and quickly adaptable solutions. In this context, mobile applications are strongly emerging as communication tools that can assist in disaster reduction. Yet, these have not been sufficiently evaluated. In view of this, the aim of this research is to evaluate the adequacy of mobile applications in disaster risk reduction in reference to some of the deadliest natural events. To this purpose, a two-part methodology is developed. Firstly, a random sample of applications is evaluated and contrasted with the literature. Secondly, the viability of mobile applications is determined based on the Digital Application Potential Index proposed by the authors, cross-referenced in Geographical Information Systems with the WorldRiskIndex. The results show that most mobile applications limit their coverage range to only one stage of Disaster Risk Management (DRM) and one type of hazard event, failing to address systemic risk and hampering the scale-up of humanitarian response. For these to become adequate and wide-reaching, strong policies to promote reliability, transparency, and citizen empowerment would be required. The policies establishing the use of mobile applications as a viable tool for DRM must consider reducing the prices of internet connectivity while increasing educational levels, on top of language translation. At this point, the adoption of mobile applications is unable to ensure DRM communication, especially in countries with higher-risk levels, requiring these to be complemented with auxiliary tools. Graphic abstract

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of the adequacy of mobile applications for disaster reduction

Corcuera

Barbero–Barrera

Hidalgo

et al. 2021

Environ Dev Sustain

View full text Add to dashboard Cite

show abstract

“…There are a number of examples of recent data innovations for flood. Examples of early warning measurement technologies include sensors [32] and unmanned aerial vehicles [33]. Examples of advances in historical trend analysis include machine learning [34] and big data analytics [35].…”

Section: Flood Data In the Ukmentioning

confidence: 99%

A Mixed-Methods Investigation into Barriers for Sharing Geospatial and Resilience Flood Data in the UK

Waterman

Casado

Bergin³

et al. 2021

Water

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With increases in average temperature and rainfall predicted, more households are expected to be at risk of flooding in the UK by 2050. Data and technologies are increasingly playing a critical role across public-, private- and third-sector organisations. However, barriers and constraints exist across organisations and industries that limit the sharing of data. We examine the international context for data sharing and variations between data-rich and data-sparse countries. We find that local politics and organisational structures influence data sharing. We focus on the case study of the UK, and on geospatial and flood resilience data in particular. We use a series of semi-structured interviews to evaluate data sharing limitations, with particular reference to geospatial and flood resilience data. We identify barriers and constraints when sharing data between organisations. We find technological, security, privacy, cultural and commercial barriers across different use cases and data points. Finally, we provide three long-term recommendations to improve the overall accessibility to flood data and enhance outcomes for organisations and communities.

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“…EWIN is one step ahead—it has been tested in real hydrometeorological phenomena and the system has worked in a favorable way, as shown in this document. A detailed comparison of various early warning systems is found in the paper “Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review” [ 16 ]. EWIN follows the latest methods and recommendations for this type of system; it can be placed on par with the latest flood alert systems that use IoT technology.…”

Section: Introductionmentioning

confidence: 99%

Flash Flood Early Warning System in Colima, Mexico

Ibarreche

Aquino

Edwards

et al. 2020

Sensors

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This paper presents a system of sensors used in flash flood prediction that offers critical real-time information used to provide early warnings that can provide the minutes needed for persons to evacuate before imminent events. Flooding is one of the most serious natural disasters humans confront in terms of loss of life and results in long-term effects, which often have severely adverse social consequences. However, flash floods are potentially more dangerous to life because there is often little or no forewarning of the impending disaster. The Emergency Water Information Network (EWIN) offers a solution that integrates an early warning system, notifications, and real-time monitoring of flash flood risks. The platform has been implemented in Colima, Mexico covering the Colima and Villa de Alvarez metropolitan area. This platform consists of eight fixed riverside hydrological monitoring stations, eight meteorological stations, nomadic mobile monitoring stations called “drifters” used in the flow, and a sniffer with data muling capability. The results show that this platform effectively compiles and forwards information to decision-makers, government officials, and the general public, potentially providing valuable minutes for people to evacuate dangerous areas.

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Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review

Cited by 90 publications

References 117 publications

Assessment of the adequacy of mobile applications for disaster reduction

Assessment of the adequacy of mobile applications for disaster reduction

A Mixed-Methods Investigation into Barriers for Sharing Geospatial and Resilience Flood Data in the UK

Flash Flood Early Warning System in Colima, Mexico

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