Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images

Typhoon Hagibis passed through Japan on October 12, 2019, bringing heavy rainfall over half of Japan. Twelve banks of seven state-managed rivers collapsed, flooding a wide area. Quick and accurate damage proximity maps are helpful for emergency responses and relief activities after such disasters. I...

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Main Authors: Wen Liu, Kiho Fujii, Yoshihisa Maruyama, Fumio Yamazaki
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/4/639
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spelling doaj-d0f301eb21424ea2bcdfbb51ea1ea8402021-02-11T00:04:41ZengMDPI AGRemote Sensing2072-42922021-02-011363963910.3390/rs13040639Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity ImagesWen Liu0Kiho Fujii1Yoshihisa Maruyama2Fumio Yamazaki3Graduate School of Engineering, Chiba University, Chiba 263-8522, JapanGraduate School of Engineering, Chiba University, Chiba 263-8522, JapanGraduate School of Engineering, Chiba University, Chiba 263-8522, JapanNational Research Institute for Earth Science and Disaster Resilience, Tsukuba, Ibaraki 305-0006, JapanTyphoon Hagibis passed through Japan on October 12, 2019, bringing heavy rainfall over half of Japan. Twelve banks of seven state-managed rivers collapsed, flooding a wide area. Quick and accurate damage proximity maps are helpful for emergency responses and relief activities after such disasters. In this study, we propose a quick analysis procedure to estimate inundations due to Typhoon Hagibis using multi-temporal Sentinel-1 SAR intensity images. The study area was Ibaraki Prefecture, Japan, including two flooded state-managed rivers, Naka and Kuji. First, the completely flooded areas were detected by two traditional methods, the change detection and the thresholding methods. By comparing the results in a part of the affected area with our field survey, the change detection was adopted due to its higher recall accuracy. Then, a new index combining the average value and the standard deviation of the differences was proposed for extracting partially flooded built-up areas. Finally, inundation maps were created by merging the completely and partially flooded areas. The final inundation map was evaluated via comparison with the flooding boundary produced by the Geospatial Information Authority (GSI) and the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) of Japan. As a result, 74% of the inundated areas were able to be identified successfully using the proposed quick procedure.https://www.mdpi.com/2072-4292/13/4/639Typhoon Hagibisinundationbackscattering modelSentinel-1
collection DOAJ
language English
format Article
sources DOAJ
author Wen Liu
Kiho Fujii
Yoshihisa Maruyama
Fumio Yamazaki
spellingShingle Wen Liu
Kiho Fujii
Yoshihisa Maruyama
Fumio Yamazaki
Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images
Remote Sensing
Typhoon Hagibis
inundation
backscattering model
Sentinel-1
author_facet Wen Liu
Kiho Fujii
Yoshihisa Maruyama
Fumio Yamazaki
author_sort Wen Liu
title Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images
title_short Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images
title_full Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images
title_fullStr Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images
title_full_unstemmed Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images
title_sort inundation assessment of the 2019 typhoon hagibis in japan using multi-temporal sentinel-1 intensity images
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-02-01
description Typhoon Hagibis passed through Japan on October 12, 2019, bringing heavy rainfall over half of Japan. Twelve banks of seven state-managed rivers collapsed, flooding a wide area. Quick and accurate damage proximity maps are helpful for emergency responses and relief activities after such disasters. In this study, we propose a quick analysis procedure to estimate inundations due to Typhoon Hagibis using multi-temporal Sentinel-1 SAR intensity images. The study area was Ibaraki Prefecture, Japan, including two flooded state-managed rivers, Naka and Kuji. First, the completely flooded areas were detected by two traditional methods, the change detection and the thresholding methods. By comparing the results in a part of the affected area with our field survey, the change detection was adopted due to its higher recall accuracy. Then, a new index combining the average value and the standard deviation of the differences was proposed for extracting partially flooded built-up areas. Finally, inundation maps were created by merging the completely and partially flooded areas. The final inundation map was evaluated via comparison with the flooding boundary produced by the Geospatial Information Authority (GSI) and the Ministry of Land, Infrastructure, Transport, and Tourism (MLIT) of Japan. As a result, 74% of the inundated areas were able to be identified successfully using the proposed quick procedure.
topic Typhoon Hagibis
inundation
backscattering model
Sentinel-1
url https://www.mdpi.com/2072-4292/13/4/639
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