Real-time Tsunami Inundation and Damage Forecast
Learning lessons from the 2011 Great East Japan Earthquake and Tsunami disaster, we develop a novel real-time tsunami inundation and damage forecast system. The forecast system consists of rapid tsunami source modeling, propagation and inundation simulation, and damage mapping with a High-Performance Computing Infrastructure. The target is the tsunamigenic earthquakes that occur along the Nankai Trough and its vicinity. Especially, the most concerned target is the Nankai Trough earthquake which is estimated to occur in next 30 years with 80 % of probability by the long-term evaluation of seismic activity in Japan. The system has been under operation as a function of the emergency response of Cabinet Office of Japan since 2018. Our newly-founded spin-off technology firm "RTi-cast" is taking a role of offering and operating real-time tsunami inundation damage forecast services.
Remote Sensing for Mapping Disaster Impact
One of the most important aspects of post-disaster response and relief is to understand the full extent of the damage. Immediately after the occurrence of a major disaster such as an earthquake or a tsunami, the information from the severely damaged area is fragmented, making it difficult to comprehend the full extent of the damage, and also making rescue and recovery activities in the affected area difficult. We are taking remote sensing approaches to achieve a breakthrough in the above problems. There are various combinations of remote sensing platforms, sensors and analysis methods. We are particularly interested in developing novel sensing and image analysis methods with advanced machine learning.
Koshimura, S., L. Moya, E. Mas, Y. Bai, Tsunami Damage Detection with Remote Sensing: A Review, Geosciences, 10(5), 177, 2020. doi:10.3390/geosciences10050177
Moya, L., Muhari, A., Adriano, B., Koshimura, S., Mas, E., Marval-Perez, L. R., Yokoya, N., Detecting urban changes using phase correlation and ℓ1-based sparse model for early disaster response: A case study of the 2018 Sulawesi Indonesia earthquake-tsunami, Remote Sensing of Environment, 242(6), 2020. doi:10.1016/j.rse.2020.111743
Inoue, T., T. Abe, S. Koshimura, A. Musa, Y. Murashima, H. Kobayashi, Development and Validation of a Tsunami Numerical Model with the Polygonally Nested Grid System and its MPI-Parallelization for Real-Time Tsunami Inundation Forecast on a Regional Scale, Journal of Disaster Research, Vol.14, No.3, pp.416-434, 2019. doi: 10.20965/jdr.2019.p0416
Musa, A., O. Watanabe, H. Matsuoka, H. Hokari, T. Inoue, Y. Murashima, Y. Ohta, R. Hino, S. Koshimura, H. Kobayashi, Real-Time Tsunami Inundation Forecast System for Tsunami Disaster Prevention and Mitigation, Journal of Supercomputing, pp.1-21, 2018. https://doi.org/10.1007/s11227-018-2363-0
Bai, Y., E. Mas, S. Koshimura, Towards operational satellite-based damage-mapping using U-net convolutional network: A case study of 2011 Tohoku earthquake-Tsunami, Remote Sensing, 10, 1626, 2018. doi:10.3390/rs10101626
Co-Founder and CTO of RTi-cast, Inc.
Visiting Researcher of RIKEN AIP Center