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Urban Sci. 2017, 1(1), 7; doi:10.3390/urbansci1010007

Physical Flood Vulnerability Mapping Applying Geospatial Techniques in Okazaki City, Aichi Prefecture, Japan

1
Department of Environmental Science and Engineering, Yamaguchi University, 2-16-1 Tokiwadai, Ube 755-8611, Japan
2
Integrated Research System for Sustainability Science (IR3S), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, 7-3-1 hongo, Bunkyo-ku, Tokyo 113-8654, Japan
3
Faculty of Fisheries and Marine Science, Brawijaya University, Jl. Veteran Malang, East Java 65145, Indonesia
*
Author to whom correspondence should be addressed.
Academic Editor: Michael Peter Smith
Received: 21 December 2016 / Revised: 20 January 2017 / Accepted: 24 January 2017 / Published: 28 January 2017
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Abstract

Flooding has been increasing since 2004 in Japan due to localized heavy rainfall and geographical conditions. Determining areas vulnerable to flooding as one element of flood hazard maps related to disaster management for urban development is necessary. This research integrated Remote Sensing data, the Geography Information System (GIS) method and Analytical Hierarchy Process (AHP) calculation to determine the physical flood-vulnerable area in Okazaki City. We developed this research by applying data from the Geospatial Information Authority of Japan (GSI) to generate the slope map and drainage density; AMEDAS (Automated Meteorological Data Acquisition System) from the Japan Meteorological Agency (JMA) to generate the rainfall data; Soil map from the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) data; and Sentinel-2 imagery to generate the land cover map. We applied the AHP calculation for weighting pairwise the parameters by comparing five iterations of the normalized matrix. We utilized the spatial analysis tool in ArcGIS to run the pairwise comparison to adjudicate the distribution of flooding according to the AHP procedure. The percentage of relative weight was slope (43%), drainage density (20%), rainfall intensity (17%), then both infiltration rate and land cover (10%). The consistency value was reasonable: consistency index (CI—0.007) and consistency ratio (CR—0.6%). We generated high accuracy for flood vulnerability prediction; 0.88 for Probability of Detection (POD), 0.28 for Probability of False Detection (POFD), 0.44 for Critical Success Index (CSI), 1.9 for Bias, and 95 of Area under Curve (AUC). The flood vulnerability was matched to the flood inundation survey of Okazaki City in August 2008 and indicated an excellent Relative Operating Characteristic (ROC). View Full-Text
Keywords: flood vulnerability; Analytical Hierarchy Process (AHP); Geography Information System (GIS); Remote Sensing; Probability of Detection (POD); Probability of False Detection (POFD); Critical Success Index (CSI); Relative Operating Characteristic (ROC) flood vulnerability; Analytical Hierarchy Process (AHP); Geography Information System (GIS); Remote Sensing; Probability of Detection (POD); Probability of False Detection (POFD); Critical Success Index (CSI); Relative Operating Characteristic (ROC)
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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

Rimba, A.B.; Setiawati, M.D.; Sambah, A.B.; Miura, F. Physical Flood Vulnerability Mapping Applying Geospatial Techniques in Okazaki City, Aichi Prefecture, Japan. Urban Sci. 2017, 1, 7.

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