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International Affairs Students Current Students Alumni Faculty/Staff Careers--> TOHOKU UNIVERSITYCREATING GLOBAL EXCELLENCE Search 日本語 Contact Tohoku University --> About Facts & Figures Facilities Organization Chart History President's Message Top Global University Project Designated National University Global Network Promotional Videos Academics Undergraduate Graduate Courses in English Exchange Programs Summer Programs Double Degree Programs Academic Calendar Syllabus Admissions Undergraduate Admissions Graduate Admissions Fees and Expenses Financial Aid Research Feature Highlights Research Releases University Research News Research Institutes Visitor Research Center Research Profiles Academic Research Staff Campus Life International Support Office IT Services Facilities Dining & Shops Campus Bus Clubs & Circles News University News Research--> Arts & Culture Health & Sports Campus & Community Press Release--> International Visit Alumni Careers Events Exhibits Music Special Event Lecture Alumni--> Map & Directions Campus Maps & Bus--> Facilities Map--> TOHOKUUNIVERSITY About Academics Admissions Research Campus Life News Events International Affairs Students Current Students Alumni Faculty/Staff Promotional Videos Subscribe to our Newsletter Map & Directions Contact Jobs & Vacancies Emergency Information Site Map 日本語 Close Home Research News Using the Past to Predict the Future: The Case of Typhoon Hagibis Research News Using the Past to Predict the Future: The Case of Typhoon Hagibis 2020-07-16 The past is often the window to our future, especially when it comes to natural disasters. Using data from the 2018 floods that struck southwestern Japan to calibrate a machine learning model, researchers from the International Research Institute of Disaster Science (IRIDeS) at Tohoku University and the Japan-Peru Center for Earthquake Engineering Research and Disaster Mitigation (CISMID, in Spanish), have successfully identified the flooding caused by Typhoon Hagibis. Typhoon Hagibis devastated Japan in October 2019, killing 91 people, damaging 85,000 homes, and causing approximately $15 billion in damage. Flooding across the affected regions was profound. In natural disaster rescue and recovery efforts, real-time flood mapping is crucial. It allows governments to direct relief to the areas that need it most. To aid this effort, satellite images using artificial intelligence (AI) are often employed. The areas and satellite images used for building the machine learning model (2018 heavy rainfall, Mabi town) and to estimate floods of an unknown event (2019 Hagibis typhoon, Koriyama and Iwaki cities)©︎Tohoku University Crucial to this is training data. Training data allows the algorithms to learn data and produce outputs when new inputs arise in a process known as machine learning. However, the amount of training data is limited in many cases. Collecting training data immediately following a disaster is costly, time-consuming and many times impossible. At IRIDeS and CISMID, authors of the study, evaluated the performance of a model to learn from the 2018 floods that struck southwestern Japan, and to identify the floods induced by the 2019 Typhoon Hagibis. The resulting flood maps were consistent with the results of actual flooding maps released by local governments and public institutions. The authors note that "Our model successfully identifies the inundated areas and verified that AI can learn from past disasters, ultimately allowing us to better predict flooding in future events." They add that "Our next step in this project would be to incorporate data from the unknown event into a second stage of training for a more accurate estimation." Publication Details: Title: Learning from the 2018 Wester Japan Heavy Rains to Detect Floods during the 2019 Hagibis TyphoonAuthors: Luis Moya, Erick Mas, and Shunichi Koshimura Journal: Remote Sensing DOI: https://doi.org/10.3390/rs12142244 Press release in Japanese Contact: Erick MasInternational Research Institute of Disaster Science, Tohoku University Tel:+81-22-752-2080Email: masirides.tohoku.ac.jp Archives 2014&＃24180; 2015&＃24180; 2016&＃24180; 2017&＃24180; 2018&＃24180; 2019&＃24180; 2020&＃24180; 2021&＃24180; 2022&＃24180; 2023&＃24180; Page Top About Tohoku University Academics Admissions Research Campus Life News Events International Affairs Students Alumni Promotional Videos Subscribe to our Newsletter Map & Directions Contact Tohoku University Jobs & Vacancies Emergency Information Site Map Media Enquiries Parent & Family Support Public Facilities Contact Tohoku University