Identifying elements that affect the probability of buildings to suffer flooding in urban areas using Google Street View. A case study from Athens metropolitan area in Greece.pdfVIP

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Identifying elements that affect the probability of buildings to suffer flooding in urban areas using Google Street View. A case study from Athens metropolitan area in Greece.pdf

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Identifying elements that affect the probability of buildings to suffer flooding in urban areas using Google Street View. A case study from Athens metropolitan area in Greece.pdf

International Journal of Disaster Risk Reduction 22 (2017) 1–9 Contents lists available at ScienceDirect International Journal of Disaster Risk Reduction journal homepage: /locate/ijdrr Identifying elements that a?ect the probability of buildings to su?er ?ooding in urban areas using Google Street View. A case study from Athens metropolitan area in Greece Michalis Diakakisa,b,c,?, Georgios Deligiannakisa,b,c, Aggelos Pallikarakisa,b,c, Michalis Skordoulisa,b,c a Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, Athens, Greece b Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, Athens, Greece c School of Business and Economics, Piraeus University of Applied Sciences, Athens, Greece MARK ARTICLE INFO Keywords: Flood probability Google street view Building vulnerability Urban ?oods ABSTRACT Even though numerous methods have been developed to predict the vulnerability of urban areas to ?ooding, there is still room for improvement in determining the susceptibility of individual buildings. This work aims to identify characteristics that a?ect a buildings probability to su?er ?ooding and evaluate their in?uence. The study uses Google Street View to examine 1073 buildings known to have ?ooded after an extreme precipitation event in 2013 in Athens, Greece and to compare them with characteristics of buildings that did not experience ?ooding. Using logistic regression, this work investigates the in?uence of these elements. Results show that certain characteristics of buildings increase their probability to ?ood up to 4.1 times. The study develops an equation involving all in?uential elements able to predict the buildings that will su?er ?ooding on a 77% rate. 1. Introduction Floods are one of the most destructive natural hazards, inducing extensive damages on a yearly basis [4,5] and posing a signi?cant threat to human life [31]. In urban environments, ?ooding is usually more damaging as higher