Search Results - "Koshimura, Shunichi"

Model-based analysis of multi-UAV path planning for surveying postdisaster building damage by Nagasawa, Ryosuke, Mas, Erick, Moya, Luis, Koshimura, Shunichi

“…Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure…”
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Response to the 2011 Great East Japan Earthquake and Tsunami disaster by Koshimura, Shunichi, Shuto, Nobuo

“…We revisited the lessons of the 2011 Great East Japan Earthquake Tsunami disaster specifically on the response and impact, and discussed the paradigm shift of…”
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Mini Special Issue on Tsunami Numerical Modeling Benchmarks – Challenges of Tsunami Modeling Hackathon by Koshimura, Shunichi

“…Numerical simulation and modeling became an essential technology in tsunami research and disaster management. Various numerical models were proposed and…”
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Towards Operational Satellite-Based Damage-Mapping Using U-Net Convolutional Network: A Case Study of 2011 Tohoku Earthquake-Tsunami by Bai, Yanbing, Mas, Erick, Koshimura, Shunichi

“…The satellite remote-sensing-based damage-mapping technique has played an indispensable role in rapid disaster response practice, whereas the current disaster…”
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Beyond tsunami fragility functions: experimental assessment for building damage estimation by Vescovo, Ruben, Adriano, Bruno, Mas, Erick, Koshimura, Shunichi

“…Tsunami fragility functions (TFF) are statistical models that relate a tsunami intensity measure to a given building damage state, expressed as cumulative…”
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Special Issue on Disaster and Big Data Part 4 by Koshimura, Shunichi

“…The 2011 Great East Japan Earthquake and Tsunami disaster taught us many lessons. Many new findings, insights, and suggestions have been made and implemented…”
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A comparative study of the cumulant lattice Boltzmann method in a single-phase free-surface model of violent flows by Sato, Kenta, Kawasaki, Koji, Koshimura, Shunichi

“…Many coastal and ocean engineering flows, such as tsunamis inundating urban areas, tend to be violent. The characteristics of these damaging flow fields are…”
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Multi-Source Data Fusion Based on Ensemble Learning for Rapid Building Damage Mapping during the 2018 Sulawesi Earthquake and Tsunami in Palu, Indonesia by Adriano, Bruno, Xia, Junshi, Baier, Gerald, Yokoya, Naoto, Koshimura, Shunichi

“…This work presents a detailed analysis of building damage recognition, employing multi-source data fusion and ensemble learning algorithms for rapid damage…”
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Learning from multimodal and multitemporal earth observation data for building damage mapping by Adriano, Bruno, Yokoya, Naoto, Xia, Junshi, Miura, Hiroyuki, Liu, Wen, Matsuoka, Masashi, Koshimura, Shunichi

“…Earth observation (EO) technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to continuously monitor ever-growing…”
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Preliminary Observations and Impact in Japan of the Tsunami Caused by the Tonga Volcanic Eruption on January 15, 2022 by Imamura, Fumihiko, Suppasri, Anawat, Arikawa, Taro, Koshimura, Shunichi, Satake, Kenji, Tanioka, Yuichiro

“…The tsunami caused by the Tonga submarine volcanic eruption that occurred at 13:15 Japan Time (JST) on January 15, 2022, exposed a blind spot in Japan’s…”
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Lessons Learned from the 2011 Great East Japan Tsunami: Performance of Tsunami Countermeasures, Coastal Buildings, and Tsunami Evacuation in Japan by Suppasri, Anawat, Shuto, Nobuo, Imamura, Fumihiko, Koshimura, Shunichi, Mas, Erick, Yalciner, Ahmet Cevdet

“…In 2011, Japan was hit by a tsunami that was generated by the greatest earthquake in its history. The first tsunami warning was announced 3 min after the…”
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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 by Moya, Luis, Muhari, Abdul, Adriano, Bruno, Koshimura, Shunichi, Mas, Erick, Marval-Perez, Luis R., Yokoya, Naoto

“…Change detection between images is a procedure used in many applications of remote sensing data. Among these applications, the identification of damaged…”
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Disaster Intensity-Based Selection of Training Samples for Remote Sensing Building Damage Classification by Moya, Luis, Geis, Christian, Hashimoto, Masakazu, Mas, Erick, Koshimura, Shunichi, Strunz, Gunter

“…Previous applications of machine learning in remote sensing for the identification of damaged buildings in the aftermath of a large-scale disaster have been…”
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Enhancement of Detecting Permanent Water and Temporary Water in Flood Disasters by Fusing Sentinel-1 and Sentinel-2 Imagery Using Deep Learning Algorithms: Demonstration of Sen1Floods11 Benchmark Datasets by Bai, Yanbing, Wu, Wenqi, Yang, Zhengxin, Yu, Jinze, Zhao, Bo, Liu, Xing, Yang, Hanfang, Mas, Erick, Koshimura, Shunichi

“…Identifying permanent water and temporary water in flood disasters efficiently has mainly relied on change detection method from multi-temporal remote sensing…”
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Learning from the 2018 Western Japan Heavy Rains to Detect Floods during the 2019 Hagibis Typhoon by Moya, Luis, Mas, Erick, Koshimura, Shunichi

“…Applications of machine learning on remote sensing data appear to be endless. Its use in damage identification for early response in the aftermath of a…”
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Detecting Urban Floods with Small and Large Scale Analysis of ALOS-2/PALSAR-2 Data by Gokon, Hideomi, Endo, Fuyuki, Koshimura, Shunichi

“…When a large-scale flood disaster occurs, it is important to identify the flood areas in a short time in order to effectively support the affected areas…”
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Special Issue on Disaster and Big Data Part 3 by Koshimura, Shunichi

“…The 2011 Great East Japan Earthquake and Tsunami Disaster left behind many lessons to learn, and there have since been many new findings and insights that have…”
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WITHDRAWAL – Administrative Duplicate Publication: Statistical Analysis of Japan Wood Frame Building Earthquake Debris Extent and Its Use in Road Networks in Japan by Moya, Luis, Mas, Erick, Yamazaki, Fumio, Liu, Wen, Koshimura, Shunichi

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Special Issue on the 100th Anniversary of the Great Kanto Earthquake by Hayashi, Haruo, Koshimura, Shunichi

“…On September 1, 1923, the Great Kanto Earthquake struck the Tokyo metropolitan area of Japan. It was an extremely powerful earthquake that caused a great fire…”
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Stochastic renewal process model of time-variant tsunami hazard assessment under nonstationary effects of sea-level rise due to climate change by Alhamid, Abdul Kadir, Akiyama, Mitsuyoshi, Aoki, Koki, Koshimura, Shunichi, Frangopol, Dan M.

“…•A framework for time-variant tsunami hazard assessment considering nonstationary sea-level rise effects is established.•Non-Poisson renewal process models are…”
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