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Open AccessArticle

Rapid Multi-Dimensional Impact Assessment of Floods

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ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040 Madrid, Spain
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Innovation and Technology for Development Centre, Universidad Politécnica de Madrid, 28040 Madrid, Spain
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LifeD Lab, 28010 Madrid, Spain
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ETSI en Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, 28031 Madrid, Spain
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Departamento de Matemática Aplicada a las Tecnologías de la Información y las Comunicaciones, Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, 28040 Madrid, Spain
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Author to whom correspondence should be addressed.
Sustainability 2020, 12(10), 4246; https://doi.org/10.3390/su12104246
Received: 1 April 2020 / Revised: 11 May 2020 / Accepted: 15 May 2020 / Published: 22 May 2020
(This article belongs to the Section Sustainable Urban and Rural Development)
Natural disasters affect hundreds of millions of people worldwide every year. The impact assessment of a disaster is key to improve the response and mitigate how a natural hazard turns into a social disaster. An actionable quantification of impact must be integratively multi-dimensional. We propose a rapid impact assessment framework that comprises detailed geographical and temporal landmarks as well as the potential socio-economic magnitude of the disaster based on heterogeneous data sources: Environment sensor data, social media, remote sensing, digital topography, and mobile phone data. As dynamics of floods greatly vary depending on their causes, the framework may support different phases of decision-making during the disaster management cycle. To evaluate its usability and scope, we explored four flooding cases with variable conditions. The results show that social media proxies provide a robust identification with daily granularity even when rainfall detectors fail. The detection also provides information of the magnitude of the flood, which is potentially useful for planning. Network analysis was applied to the social media to extract patterns of social effects after the flood. This analysis showed significant variability in the obtained proxies, which encourages the scaling of schemes to comparatively characterize patterns across many floods with different contexts and cultural factors. This framework is presented as a module of a larger data-driven system designed to be the basis for responsive and more resilient systems in urban and rural areas. The impact-driven approach presented may facilitate public–private collaboration and data sharing by providing real-time evidence with aggregated data to support the requests of private data with higher granularity, which is the current most important limitation in implementing fully data-driven systems for disaster response from both local and international actors. View Full-Text
Keywords: natural disasters; climate change; floods; resilience; mitigation; social impact; social media; mobile phone data; remote sensing; data privacy natural disasters; climate change; floods; resilience; mitigation; social impact; social media; mobile phone data; remote sensing; data privacy
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Pastor-Escuredo, D.; Torres, Y.; Martínez-Torres, M.; Zufiria, P.J. Rapid Multi-Dimensional Impact Assessment of Floods. Sustainability 2020, 12, 4246.

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