Information Technology in Disaster Risk Reduction

Name: Information Technology in Disaster Risk Reduction | 6th IFIP WG 5.15 International Conference, ITDRR 2021, Morioka, Japan, October 25-27, 2021, Revised Selected Papers
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6th IFIP WG 5.15 International Conference, ITDRR 2021, Morioka, Japan, October 25-27, 2021, Revised Selected Papers

Jun Sasaki Yuko Murayama Dimiter Velev Plamena Zlateva(Editor)

Springer (Publisher)

Published on 13. April 2022

X, 177 pages

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978-3-031-04170-9 (ISBN)

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Content

Intro
Preface
Organization
Contents
Information Analysis for Situation Awareness
Automatic Calculation of Damage Rate of Roofs Based on Image Segmentation
1 Introduction
1.1 Problem in Building Damage Investigation
1.2 Usage of Aerial Photos Images During Disaster
1.3 Study Purpose
2 Previous Study
3 Development of Automatic Method to Calculate the Rate of Damage on Roof
3.1 The Method to Calculate the Rate of Damage on the Roof in the Building Damage Investigation
3.2 The Method to Calculate Damage Rate of Roof in This Study
3.3 Trimming Algorithm
3.4 Shortcomings of this Study
3.5 Increase of Data by Division of Roof Surface
4 Division of Roof Surface
4.1 Previous Study About Roof Surface
4.2 Segmentation Model
4.3 Used Data
4.4 Training Method
4.5 Result of Division in the First Experiment
4.6 Roof Image with Some Features
4.7 Result of Division in Additional Experiment
4.8 Image Processing After Division
5 Classification of Damage Degree
5.1 Classification Model
5.2 Data Used
5.3 Training Method
5.4 Classification Result
6 Calculation of Damage Rate
6.1 Calculation Method of Estimated Damage Rate
6.2 Error of Correct Answer
6.3 Comparison of Correct Damage Rate and Estimated Damage Rate
6.4 Evaluation of Model Accuracy
7 Discussion and Future Tasks
References
Flood Disaster Mitigation System Adopting Meteorological Data and Geographic Information Systems
1 Introduction
2 Related Work
3 System Design Requirement Analysis of FDMS Using SD
3.1 Outlines of SD
3.2 Iceberg Model Analysis
3.3 Causal Loop Diagram Analysis
3.4 Leverage Points
3.5 Observed Data Examples at River
3.6 System Concept
4 Basic Design and Integration of System
4.1 Basic Design of System
4.2 Integration of System
5 System Verification
6 Conclusion
References
Flood Disaster Management System for Situation Awareness and Response Using Twitter Data
1 Introduction
2 Related Work
2.1 Situation Awareness
2.2 Usage of Social Media for Situation Awareness During Disasters
2.3 Disaster Response and Relief
2.4 Originality of the Present Study
3 System Design
3.1 System Configuration
3.2 Data Collection
3.3 Extraction of Information Location
3.4 Web Application
3.5 Situation Awareness
4 System Development
4.1 System Frontend
4.2 System Backend
4.3 System Operation Environment
4.4 Operation Target Area
5 Conclusion
References
Evacuation and Rescue
Proposed Evacuation Behavior Model Using Open-Source Data: Flood Disaster Case Study
1 Introduction
2 Related Studies
3 Evacuation Model Concept
3.1 Evacuation Decision Process Model
3.2 Calculation of Evacuation Shelter Choice Probability
3.3 Evacuee Rate Calculation
4 Simulation
4.1 Algorithm Overview
4.2 Target Area and Data
4.3 Data Used in the Simulation
4.4 Explanatory Variables
4.5 Scenarios
4.6 Optimization Method
4.7 Comparison Between Actual and Predicted Number of Evacuees
4.8 Field Survey
5 Conclusion
References
Agent-Based Tsunami Crowd Evacuation Simulation for Analysis of Evacuation Start Time and Disaster Rate in Zushi City
1 Introduction
2 Methods
2.1 Modelling of Target Areas
2.2 Tsunami Model and Evacuation Behaviour of Agents
3 Results and Discussion
4 Conclusion
References
Rescue Strategy in Case of Large-Scale Flood Damage in the Koto Delta Region
1 Introduction
2 Research Background
2.1 Characteristics of Flooding in the Koto Delta Region
2.2 Issues of Wide-Area Evacuation
3 Previous Studies and Purpose of this Study
4 Estimation of Changes in the Number of Isolated People in the Koto Delta Region When Rescue Operations are Conducted
4.1 Data and Estimation Methods
4.2 Comparison of the Difference in the Size of Population Aggregation Unit Area
4.3 Comparison of the Difference in the Order of Rescuing Isolated People
4.4 Comparison of the Difference in the Evacuation Rate of the Residents on Upper Floors
4.5 Estimation of the Evacuation Rate Required to Complete Rescue in 7 days
5 Summary and Future Work
References
COVID-19 Issues
Trial of Building a Resilient Face-To-Face Classroom Based on CO2-Based Risk Awareness
1 Introduction
2 Case Study and Issues
2.1 Case Study
2.2 Ventilation Issues
3 Measurement System
4 Experiments
4.1 Measurement at an Event
4.2 Measurement of the Whole Campus
5 Conclusion
References
Analysis of Quote Retweets for COVID-19 State of Emergency Related Tweets Posted from Prefectural Governors' Accounts in Japan
1 Introduction
2 Related Studies
3 Analysis of Tweets
3.1 Governors' Accounts to Be Analyzed
3.2 Tweets Collection
3.3 Analysis of Quote Retweets of Governors' Tweets
4 Conclusions
References
Insights from the COVID-19 Pandemic for Systemic Risk Assessment and Management
1 Introduction
1.1 Have We Learnt Enough from COVID-19 to Manage New Pandemic Waves Better?
1.2 The Aim of This Paper and How It Is Organized
2 Characteristics of a Major Pandemic in the Globalization Era
3 Risks in the Light of Systemic Interdependencies
3.1 Adequate Risk Definition in the Presence of Dynamic Complexity
3.2 Quantitative Analysis of Qualitative Models of Systemic Risk
4 Order of Magnitude of Pandemic Cascading Effects
4.1 The Risk Systemicity Approach
4.2 Cascading Effects as Vicious Cycles
5 Discussion
References
IT Use for Risk and Disaster Management
Leveraging Geospatial Technology in Disaster Management
1 Introduction
1.1 Disaster Scenario
1.2 Geospatial Technology
1.3 Geospatial Technology Innovations in Disaster Management
2 Karnataka State Disaster Management Information System (KSDMIS) - A Geospatial Web Application for Collecting Data on Disaster Events
2.1 About Karnataka
2.2 Objectives of KSDMIS Application Software
2.3 Benefits of KSDMIS Application Software
2.4 KSDMIS Application Software Structure
2.5 Mobile Interface for Data Collection and Updation
2.6 Web Interface to the KSDMIS Application Software
2.7 Adopting Geospatial Technology in KSDMIS
3 Geospatial Enabled - District Disaster Management Plan - GEDDMP System
3.1 Operation Strategy
3.2 Continuous Data Updation
3.3 Benefits of Geospatial Enabled-DDMP System
3.4 Geospatial Technology for Different Phases of Disaster Management
3.5 Geospatial Enabled DDMP Application Software Structure
3.6 Core Technology of Geospatial-DDMP Application Software
3.7 Workflow
3.8 Features of Survey Template HOOKs
3.9 Roadmap and Futuristic View
References
Information Technologies for Assessing the Effectiveness of the Quarantine Measures
1 Importance of Quarantine Measures
2 Variety of Quarantine Measures
3 Application of Restrictive Measures and the Need to Assess Their Efficiency
4 Selection of Modelling Approach for Quarantine Measure Efficiency
5 Overview of Epidemiology Models
6 Model Description and Development of Software
7 Model Description and Software Development
8 Discussion of Modelling Results
9 Scope of Application and Further Improvement of the Simulation Tool
10 Comparison of Modeling Results
11 Conclusions
References
Author Index

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Information Technology in Disaster Risk Reduction

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