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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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/4/639 |
| _version_ | 1797411652658790400 |
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| author | Wen Liu Kiho Fujii Yoshihisa Maruyama Fumio Yamazaki |
| author_facet | Wen Liu Kiho Fujii Yoshihisa Maruyama Fumio Yamazaki |
| author_sort | Wen Liu |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T04:49:14Z |
| format | Article |
| id | doaj.art-d0f301eb21424ea2bcdfbb51ea1ea840 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T04:49:14Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d0f301eb21424ea2bcdfbb51ea1ea8402023-12-03T13:12:17ZengMDPI AGRemote Sensing2072-42922021-02-0113463910.3390/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, Chiba 263-8522, JapanGraduate School of Engineering, Chiba University, Chiba, Chiba 263-8522, JapanGraduate School of Engineering, Chiba University, Chiba, 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 |
| 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 |
| title | 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_short | 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 |
| topic | Typhoon Hagibis inundation backscattering model Sentinel-1 |
| url | https://www.mdpi.com/2072-4292/13/4/639 |
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