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Geosciences 2017, 7(4), 123; doi:10.3390/geosciences7040123

Flood Risk Assessment in Urban Areas Based on Spatial Analytics and Social Factors

1
Geomatics Engineering, Department of Earth & Space Science & Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada
2
Canada Centre for Mapping and Earth Observation, Nature Resources Canada, Ottawa, ON K1S 5K2, Canada
*
Author to whom correspondence should be addressed.
Received: 1 November 2017 / Revised: 15 November 2017 / Accepted: 22 November 2017 / Published: 27 November 2017
(This article belongs to the Special Issue Integrated Risk Analysis and Management of Floods)
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Abstract

Flood maps alone are not sufficient to determine and assess the risks to people, property, infrastructure, and services due to a flood event. Simply put, the risk is almost zero to minimum if the flooded region is “empty” (i.e., unpopulated, has not properties, no industry, no infrastructure, and no socio-economic activity). High spatial resolution Earth Observation (EO) data can contribute to the generation and updating of flood risk maps based on several aspects including population, economic development, and critical infrastructure, which can enhance a city’s flood mitigation and preparedness planning. In this case study for the Don River watershed, Toronto, the flood risk is determined and flood risk index maps are generated by implementing a methodology for estimating risk based on the geographic coverage of the flood hazard, vulnerability of people, and the exposure of large building structures to flood water. Specifically, the spatial flood risk index maps have been generated through analytical spatial modeling which takes into account the areas in which a flood hazard is expected to occur, the terrain’s morphological characteristics, socio-economic parameters based on demographic data, and the density of large building complexes. Generated flood risk maps are verified through visual inspection with 3D city flood maps. Findings illustrate that areas of higher flood risk coincide with areas of high flood hazard and social and building exposure vulnerability. View Full-Text
Keywords: flood risk; spatial analytics; hazard; social vulnerability; GIS modelling flood risk; spatial analytics; hazard; social vulnerability; GIS modelling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Armenakis, C.; Du, E.X.; Natesan, S.; Persad, R.A.; Zhang, Y. Flood Risk Assessment in Urban Areas Based on Spatial Analytics and Social Factors. Geosciences 2017, 7, 123.

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