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  • Risk Management for Tsunami-Related Disasters
Risk Management for Tsunami-Related Disasters
  • Unit 1 - Lessons from the past tsunami events and future perspectives 1

    • Lecture1.1
      We revisit the lessons of the past catastrophic tsunami events, e.g. the 2011 Japan and 2004 Indian Ocean, specifically on the response and impact, and discuss the paradigm shift of tsunami disaster management policies and the perspectives for future tsunami disaster mitigation. Revisiting the modern histories of Tohoku tsunami disasters and pre-2011 tsunami countermeasures, we clarify how Japan’s coastal communities have prepared for tsunami. The discussion mainly focuses on structural measures such as seawalls and breakwaters and non-structural measures of hazard map and evacuation. The responses to the 2011 event are discussed specifically on the tsunami warning system and efforts to identify the tsunami impacts. The post tsunami survey results shed the light on the mechanisms of structural destruction, tsunami loads, and structural vulnerability to inform structural rehabilitation measures and land use planning.
  • Unit 2 - Tsunamis: modeling technology and its application for tsunami warning 1

    • Lecture2.1
      This lecture gives an overview of tsunami modeling and its application on monitoring and warning systems which are arranged to five sections: 1) Tsunami generation mechanism, 2) Numerical approach, 3) Tsunami monitoring system, 4) Tsunami warning system and 5) Lessons from recent tsunamis. Audiences of this lecture will understand limitation of the current tsunami modeling and warning system and be able to understand or convey proper tsunami warning message as well as perform safer evacuation related actions.
  • Unit 3 - Tsunami Effects on Infrastructure 1

    • Lecture3.1
      Extreme coastal floods such as the 2004 Indian Ocean Tsunami, the 2010 Chile Tsunami or the 2011 Tohoku Tsunami, as well as by the 2005 Katrina and 2012 Sandy hurricanes have shown that, hydrodynamic and debris loading are major contributors to the extreme damage experienced by coastal infrastructure. The course will provide an overview of the effects of tsunamis on coastal infrastructure and of the world’s first design standard for tsunami resistant structures. The new ASCE-7 Tsunami Loads and Effects Committee (of which Prof. Nistor is a Voting Member) has recognized the significant importance of tsunami-induced hydrodynamic and debris loading and proposed a comprehensive document (ASCE7 Chapter 6) for the design of critical infrastructure.
  • Unit 4 - Artificial Intelligence and Remote sensing technology for tsunami damage 1

    • Lecture4.1
      The focus of this lecture is on the application of artificial intelligence and Earth observation technologies for extracting tsunami-induced damage in urban areas. We will learn how the advance of machine learning framework together with multisource remote sensing imagery enables rapid and accurate damage recognition soon after tsunami disasters. Here, some of the state-of-the-art algorithms used for damage mapping will be explored. Finally, we will see examples of applications in previous disaster events such as the 2018 Sulawesi Tsunami in Indonesia.
  • Unit 5 - Modeling tsunami evacuations 1

    • Lecture5.1
      This course lecture presents the methodologies for assessing tsunami evacuation trough simulation and modeling. The discussion focuses on the use of agent based modeling (ABM) as a tool to assess the evacuation behavior and contribute to tsunami risk reduction. The lecture presents several cases of tsunami evacuation studies and applications to evacuation planning. In addition, an open-source agent based platform is presented and the steps to develop, modify and use it for evacuation simulation are briefly discussed. The lecture aims on giving a short introduction to the use of ABM in disaster research, and in particular, tsunami evacuation research.
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    Prev This lecture gives an overview of tsunami modeling and its application on monitoring and warning systems which are arranged to five sections: 1) Tsunami generation mechanism, 2) Numerical approach, 3) Tsunami monitoring system, 4) Tsunami warning system and 5) Lessons from recent tsunamis. Audiences of this lecture will understand limitation of the current tsunami modeling and warning system and be able to understand or convey proper tsunami warning message as well as perform safer evacuation related actions.
    Next The focus of this lecture is on the application of artificial intelligence and Earth observation technologies for extracting tsunami-induced damage in urban areas. We will learn how the advance of machine learning framework together with multisource remote sensing imagery enables rapid and accurate damage recognition soon after tsunami disasters. Here, some of the state-of-the-art algorithms used for damage mapping will be explored. Finally, we will see examples of applications in previous disaster events such as the 2018 Sulawesi Tsunami in Indonesia.

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    El Comité de Gestión del Riesgo de Desastres (CDRM, por sus siglas en inglés) es uno de los comités técnicos permanentes de la World Federation of Engineering Organizations (WFEO)

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