Responding to Extreme Weather Events
Hydrometeorological Extreme Events
1. Edition February 2024
416 Pages, Hardcover
Wiley & Sons Ltd
ISBN:
978-1-119-74158-9
John Wiley & Sons
Further versions
RESPONDING TO EXTREME WEATHER EVENTS
An up-to-date discussion of the latest in weather-related event forecasting and management
In Responding to Extreme Weather Events, a team of distinguished researchers delivers a timely and authoritative exploration of three international extreme weather projects: ANYWHERE, I-REACT, and BeAWARE. The key contributions from policymaking, science, and industry in each project are discussed, as are the resulting improved measures and technologies for forecasting and managing weather-related extreme events.
The authors cover the entire crisis management cycle, from awareness and early warning to effective responses to extreme weather events. Readers will also find:
* A thorough introduction to the science and policy background of managing extreme weather events
* Comprehensive explorations of impact forecasting for extreme weather events, including discussion of the ANYWHERE project
* Practical discussions of how to improve resilience to weather-related emergencies with advanced cyber technologies, including discussion of the I-REACT project
* A novel framework for crisis management during extreme weather events, including discussion of the BeAWARE project
Essential for disaster management professionals, Responding to Extreme Weather Events will also benefit academic staff and researchers with an interest in extreme weather events and their consequences.
List of Contributors xii
Series Preface xvi
1 The ANYWHERE Paradigm Shift in Responding to Weather and Climate Emergencies: Impact Forecasting, Dynamic Vulnerability and the Need for Citizen's Involvement 1
Daniel Sempere- Torres and Marc Berenguer
1.1 Disaster Risk Management in Times of Climate Change: The Need of a Proactive Approach 1
1.2 Adapting Risk Management to the 'New Normality': The Case of Flood Risk Management 2
1.3 Changing the Paradigm: Impact- Based Multi- Hazard Early Warning Systems to Move from Reactive to Pro- Active Emergency Response Strategies 4
1.3.1 From Reactive to Proactive Emergency Response Strategies 5
1.3.2 The ANYWHERE MH- IEWS 9
1.4 The New Paradigm: Dynamic Vulnerability 13
1.5 Future Work: From Multi- Hazards to Multi- Risk IEWS 16
Notes 17
References 18
2 Hydrometeorological Drought Forecasts: Lessons Learned from ANYWHERE and Next Steps to Improve Drought Management 23
Samuel J. Sutanto and Henny A.J. Van Lanen
2.1 Introduction 23
2.2 Method for Forecasting Hydrometeorological Droughts 25
2.2.1 The Climate (ECMWF SEAS5) and Hydrological (LISFLOOD) Models 25
2.2.2 The Drought Indices 26
2.2.3 The Drought Forecast Algorithms 28
2.3 Hydrometeorological Drought Forecasts 30
2.3.1 Meteorological Drought Forecasts 30
2.3.2 Hydrological Drought Forecasts 31
2.4 Drought Forecast Performance 33
2.4.1 The Origin of Seasonal Drought Forecast Skill 33
2.4.2 Examples of Assessment of Seasonal Drought Forecast Performance 34
2.5 Importance of Catchment Memory 38
2.6 Outlook and Future Improvements 40
2.6.1 Drought Impact Forecasts 41
2.6.2 Compound and Cascading (CC) Dry Hazards 43
References 44
3 Experiences and Lessons Learnt in Wildfire Management with PROPAGATOR, an Operational Cellular- Automata- Based Wildfire Simulator 49
Andrea Trucchia, Mirko D'Andrea, Francesco Baghino, Nicolò Perello, Nicola Rebora, and Paolo Fiorucci
3.1 Introduction 49
3.1.1 Mathematical Models for Wildfire Management 50
3.2 Synopsis of Propagator Development: More than a Decade of Wildfire Simulations 52
3.3 Propagator Model 55
3.4 Case Studies 62
3.4.1 Data Retrieval 62
3.5 Results and Discussion 65
3.5.1 Performance Indicators 65
3.5.2 Performances of Test Cases 70
3.5.3 An Example of Continuous Improvement and Operational Deployment: Implementation in Ireland 71
3.6 Conclusions 71
References 73
4 Building an Operational Decision Support System for Multiple Weather- Induced Health Hazards: ANYWHERE Developments and Future Applications 77
Claudia Di Napoli
4.1 Introduction 77
4.2 Heatwave Prediction in ANYWHERE 79
4.2.1 The Universal Thermal Climate Index 80
4.2.2 Forecasting Algorithms 80
4.2.3 Heatwave Products 81
4.2.4 Integration in the MH- EWS 81
4.2.5 Temperature Products 81
4.3 Air Pollution Prediction in ANYWHERE 83
4.3.1 Air Quality 83
4.3.2 Forecasting Algorithms 85
4.3.3 Air Quality Products 85
4.3.4 Integration in the MH- EWS 85
4.4 ANYWHERE MH- EWS in Action: The European 2017 Heatwave 86
4.5 Implementation at Pilot Sites 87
4.5.1 Integration of Local Heatwave and Air Pollution Products 90
4.5.2 Evaluation at Pilot Sites 92
4.6 Future Applications 93
4.6.1 Impact- Based Warnings 93
4.6.2 Multi- Hazard Forecasting 95
4.6.3 Cold Spells as a Health Hazard 97
4.6.4 Social Sensing 97
4.6.5 Protecting the Vulnerable 98
4.7 Conclusions 98
Funding 99
Acknowledgements 99
Notes 99
References 99
5 The EUMETNET OPERA Radar Network - European- Wide Precipitation Composites Supporting Rainfall- Induced Flash Flood Emergency Management 105
Shinju Park, Marc Berenguer, Daniel Sempere- Torres, and Annakaisa Von Lerber
5.1 Introduction 105
5.2 The EUMETNET OPERA Radar Precipitation Composites 106
5.3 Monitoring the Quality of the Opera Precipitation Composites 108
5.4 Application of Opera Precipitation Composites for Flash Flood Hazard Nowcasting 110
5.5 Conclusions and Outlook 113
References 116
6 Towards Impact- Based Communication During Climate Emergencies: A Community- Based Approach to Improve Flood Early Warning Systems 119
Erika Meléndez- Landaverde, Daniel Sempere- Torres, and Shinju Park
6.1 Introduction 119
6.2 Impact- Based Early Warning Systems (IB- EWS) for Actionable Decisions: Key Aspects 121
6.2.1 Partnerships for an Effective Co- Design IB- EWS 122
6.2.2 End Users: Identifying Needs for Emergency Response 123
6.2.3 Risk Identification and Impact Data Collection 124
6.2.4 Evaluation of IB- EWSs 125
6.3 The Next Step for Community- Based EWS: The Site- Specific EWS Framework (SS- EWS) 125
6.3.1 The Site- Specific Early Warning System Framework (SS- EWS) 126
6.4 The SS- EWS in Catalonia, NE Spain: Experiences and Lessons Learned 128
6.4.1 Community- Based Sessions in Terrassa: The Co- Design Process and Experiences 129
6.4.2 Community- Based Emergency Response: SS- EWS Real- Time Application in Terrassa 132
6.4.3 The Site- Specific Warnings (SSWs): Their Influence on the Risk Perception and Understanding of Users in Blanes 132
6.4.4 A4alerts: Mobile Application for Emergency Communication 134
6.5 An Outlook on Future Community and Impact- Based Communication Tools for Floods 135
Notes 137
References 137
7 Challenges for a Better Use of Crowdsourcing Information in Climate Emergency Situational Awareness and Early Warning Systems 141
Milan Kalas, Joy Ommer, Amin Shakya, Sasa Vraníc, Denys Kolokol, and Tommaso Sabattini
7.1 Introduction 141
7.2 Crowd- Generated Content to Support Emergency Management and Early Warning 143
7.2.1 Examples of the Citizen Science in Disaster Risk Management 143
7.2.2 Tools 144
7.2.3 Challenges in the Integration and Application of Citizen- Generated Content in DRM 145
7.3 ANYWHERE Applications and Their Lessons Learnt 146
7.3.1 Crowd Mapping to Support Real- Time Risk Assessment 147
7.3.2 Social Media Streaming to Increase Emergency Situational Awareness 147
7.3.3 A Crowdsourcing Solution for Collecting Information on the Magnitude and Impact of Disasters 153
7.3.4 Towards a Holistic System 155
7.3.5 Facilitating Communication Between Actors in Emergency Management 157
7.4 Conclusion 158
Note 159
References 159
8 Co- Evaluation: How to Measure Achievements in Complex Co- Production Projects? ANYWHERE's Contribution to Enhance Emergency Management of Weather and Climate Events 163
Oliver Gebhardt and Christian Kuhlicke
8.1 Introduction 163
8.2 Application of the ANYWHERE Co- Evaluation Framework 165
8.2.1 Step 1: Context Analysis 166
8.2.2 Step 2: Description of Baseline Scenario and ANYWHERE Scenario 166
8.2.3 Step 3: Selection of Suitable and Feasible Criteria 166
8.2.4 Step 4: Selection of Appropriate Co- Evaluation Method 167
8.2.5 Step 5: Data Collection 167
8.2.6 Step 6: Data Aggregation and Analysis 168
8.3 Discussion of Co- Evaluation Results 168
8.4 Discussion 176
8.5 Conclusion 177
Notes 177
References 178
9 Using Artificial Intelligence to Manage Extreme Weather Events: The Impact of the beAWARE Solution 181
Anastasios Karakostas, Stefanos Vrochidis, and Ioannis Kompatsiaris
9.1 Introduction 181
9.2 Overall Objectives of the Project 182
9.3 The Impact of beAWARE 188
9.3.1 Scientific and Innovation Impact 188
9.3.2 Economic Impact 191
9.3.3 Safety Impact 191
9.3.4 Training Impact 191
9.3.5 Policymakers 193
9.3.6 First Responders 194
9.3.7 General Public (Citizens) 195
9.4 Conclusion 196
Acknowledgement 197
References 197
10 Innovative Visual Analysis Solutions to Support Disaster Management 199
Emmanouil Michail, Panagiotis Giannakeris, Ilias Koulalis, Stefanos Vrochidis, and Ioannis Kompatsiaris
10.1 Introduction 199
10.2 Related Work 200
10.3 Methodology 203
10.3.1 Disaster Detection 204
10.3.2 Object Detection 205
10.3.3 River Level Monitoring 206
10.3.4 Drone Analysis 206
10.3.5 Traffic Analysis and Management 209
10.4 System Evaluation 211
10.4.1 Disaster Detection 212
10.4.2 Object Detection and Tracking 213
10.4.3 River Level Monitoring 215
10.4.4 Drone Analysis 217
10.4.5 Traffic Analysis and Management 219
10.5 Conclusions 221
References 221
11 Social Media Monitoring for Disaster Management 224
Stelios Andreadis, Ilias Gialampoukidis, Stefanos Vrochidis, and Ioannis Kompatsiaris
11.1 Introduction 224
11.2 Social Media Analysis 225
11.2.1 Framework Overview 225
11.2.2 Data Collection from Twitter 226
11.2.3 Analysis of Social Media Data 227
11.2.4 Data Representation 232
11.3 Social Media Clustering 234
11.3.1 Evaluation of Spatial Clustering Techniques 234
11.3.2 The Proposed Spatiotemporal Clustering 236
11.4 Visualizations 237
11.4.1 Annotation Tool 237
11.4.2 Demonstration Tool 239
11.5 Conclusion 240
Notes 241
References 241
12 Human- Centred Public Warnings 243
Claudio Rossi and Antonella Frisiello
12.1 Introduction 243
12.2 Risk Communication 245
12.2.1 Risk Communication Key Aspects 246
12.2.2 United Nation Guidelines 249
12.3 Technical Standards and Recommendations 250
12.3.1 Standards and Requirements for Public Warning Systems Implementation 250
12.3.2 The Common Alerting Protocol 251
12.3.3 Recommended System Architecture 252
12.3.4 Use of Technical Standards 257
12.3.5 Media Adaptation and Usability of Alerts 260
12.4 Future Outlooks in Public Warning and Risk Communication 267
12.4.1 Crowdsourcing Approaches 267
12.4.2 Organizational Best Practices 269
Note 271
References 272
13 A DRM Solution for Professionals and Citizens 275
Claudio Rossi, Antonella Frisiello, Gianluca Marucco, and Marco Pini
13.1 A Novel Mobile Application for DRR 275
13.2 The I- REACT Co- Design Approach 276
13.2.1 The Co- Design Process in the I- REACT Project 277
13.2.2 From Data to Specifications: The Results of I- REACT Co- Design Activities 280
13.3 The Development and Implementation of the I- REACT Mobile Solution 285
13.4 Gamified Crowdsourcing for Disaster Risk Management 290
13.5 The I- REACT Wearable Solution for First Responders 293
13.5.1 Ad- hoc Positioning Wearable Device for Enhanced Localization 294
13.5.2 Operational Scenario 295
13.5.3 Device Operating Modes 297
13.5.4 Communication Flow 299
13.5.5 Wearable Device Implementation and Prototyping Cycles 299
13.5.6 Wearable Device Performance Validation 301
13.6 Improved Positioning of First Responders Using EGNSS Technologies 302
13.6.1 A Service- Oriented Cloud- Based Architecture for Mobile Geolocated Emergency Services (EGNOS in the Cloud) 304
13.6.2 EDAS Service Selector, Decoder and Storage 306
13.6.3 Augmented PVT and Integrity Computation 307
13.6.4 Implementation of the Architecture of the Cloud Software Module 308
13.6.5 Performance Evaluation of the Implementation 309
13.6.6 Positioning Integrity Computation for Consumer- Grade GNSS Receivers 313
References 323
14 Transforming Data Coming from Social Media Streams into Disaster- Related Information 326
Claudio Rossi, Edoardo Arnaudo, Dario Salza, Giacomo Blanco, and Lorenzo Bongiovanni
14.1 Introduction 326
14.2 Natural Language Processing Methods for Emergency- Related Text Processing 331
14.2.1 Document Representation 332
14.2.2 Document Classification 333
14.2.3 Named Entity Recognition 334
14.3 Model Architecture 335
14.4 Classification Results 336
14.4.1 Bag of Words with SVM 336
14.4.2 CNN with Multilingual Word Embeddings 337
14.4.3 CNN with XML- T Contextual Word Embeddings 338
14.5 Image Filtering and Classification for Contextual Awareness 339
14.5.1 Filtering Unwanted Images 339
14.5.2 Methodology for NSFW Classification 340
14.5.3 Classifying Relevant Images 341
14.5.4 Methodology for Image Classification 343
14.6 Event Detection 345
14.6.1 Related Work 346
14.6.2 Methodology 349
14.6.3 Evaluation of the Event Detection Pipeline 351
14.7 Impact Extraction 354
14.7.1 Related Work 354
14.7.2 Methodology 356
14.7.3 Aggregating the Information 357
14.7.4 Evaluation Results 358
14.8 Annex 1: Definition of Yara Rules for Impact Estimation 360
Funding 362
Notes 362
References 362
15 Conclusions and Perspectives 368
Philippe Quevauviller
15.1 Introduction 368
15.2 Policy Background 369
15.2.1 Civil Protection Policies 370
15.2.2 EU Strategy on Adaptation to Climate Change 372
15.2.3 Water Framework and Marine Policies 373
15.2.4 Links with Projects Subject to this Book 374
15.3 Actor's Interactions and Community Building 375
15.3.1 Who are the Actors? 375
15.3.2 Community Building 377
15.4 Research Trends Related to Disaster Risks (Including Climate Extremes) in the Security Research Area 379
15.4.1 Societal Resilience 379
15.4.2 Tools for Integrated Risk Reduction for Extreme Climate Events 381
15.5 Conclusions, Gaps and Recommendations 383
Notes 384
References 384
Index 386
Series Preface xvi
1 The ANYWHERE Paradigm Shift in Responding to Weather and Climate Emergencies: Impact Forecasting, Dynamic Vulnerability and the Need for Citizen's Involvement 1
Daniel Sempere- Torres and Marc Berenguer
1.1 Disaster Risk Management in Times of Climate Change: The Need of a Proactive Approach 1
1.2 Adapting Risk Management to the 'New Normality': The Case of Flood Risk Management 2
1.3 Changing the Paradigm: Impact- Based Multi- Hazard Early Warning Systems to Move from Reactive to Pro- Active Emergency Response Strategies 4
1.3.1 From Reactive to Proactive Emergency Response Strategies 5
1.3.2 The ANYWHERE MH- IEWS 9
1.4 The New Paradigm: Dynamic Vulnerability 13
1.5 Future Work: From Multi- Hazards to Multi- Risk IEWS 16
Notes 17
References 18
2 Hydrometeorological Drought Forecasts: Lessons Learned from ANYWHERE and Next Steps to Improve Drought Management 23
Samuel J. Sutanto and Henny A.J. Van Lanen
2.1 Introduction 23
2.2 Method for Forecasting Hydrometeorological Droughts 25
2.2.1 The Climate (ECMWF SEAS5) and Hydrological (LISFLOOD) Models 25
2.2.2 The Drought Indices 26
2.2.3 The Drought Forecast Algorithms 28
2.3 Hydrometeorological Drought Forecasts 30
2.3.1 Meteorological Drought Forecasts 30
2.3.2 Hydrological Drought Forecasts 31
2.4 Drought Forecast Performance 33
2.4.1 The Origin of Seasonal Drought Forecast Skill 33
2.4.2 Examples of Assessment of Seasonal Drought Forecast Performance 34
2.5 Importance of Catchment Memory 38
2.6 Outlook and Future Improvements 40
2.6.1 Drought Impact Forecasts 41
2.6.2 Compound and Cascading (CC) Dry Hazards 43
References 44
3 Experiences and Lessons Learnt in Wildfire Management with PROPAGATOR, an Operational Cellular- Automata- Based Wildfire Simulator 49
Andrea Trucchia, Mirko D'Andrea, Francesco Baghino, Nicolò Perello, Nicola Rebora, and Paolo Fiorucci
3.1 Introduction 49
3.1.1 Mathematical Models for Wildfire Management 50
3.2 Synopsis of Propagator Development: More than a Decade of Wildfire Simulations 52
3.3 Propagator Model 55
3.4 Case Studies 62
3.4.1 Data Retrieval 62
3.5 Results and Discussion 65
3.5.1 Performance Indicators 65
3.5.2 Performances of Test Cases 70
3.5.3 An Example of Continuous Improvement and Operational Deployment: Implementation in Ireland 71
3.6 Conclusions 71
References 73
4 Building an Operational Decision Support System for Multiple Weather- Induced Health Hazards: ANYWHERE Developments and Future Applications 77
Claudia Di Napoli
4.1 Introduction 77
4.2 Heatwave Prediction in ANYWHERE 79
4.2.1 The Universal Thermal Climate Index 80
4.2.2 Forecasting Algorithms 80
4.2.3 Heatwave Products 81
4.2.4 Integration in the MH- EWS 81
4.2.5 Temperature Products 81
4.3 Air Pollution Prediction in ANYWHERE 83
4.3.1 Air Quality 83
4.3.2 Forecasting Algorithms 85
4.3.3 Air Quality Products 85
4.3.4 Integration in the MH- EWS 85
4.4 ANYWHERE MH- EWS in Action: The European 2017 Heatwave 86
4.5 Implementation at Pilot Sites 87
4.5.1 Integration of Local Heatwave and Air Pollution Products 90
4.5.2 Evaluation at Pilot Sites 92
4.6 Future Applications 93
4.6.1 Impact- Based Warnings 93
4.6.2 Multi- Hazard Forecasting 95
4.6.3 Cold Spells as a Health Hazard 97
4.6.4 Social Sensing 97
4.6.5 Protecting the Vulnerable 98
4.7 Conclusions 98
Funding 99
Acknowledgements 99
Notes 99
References 99
5 The EUMETNET OPERA Radar Network - European- Wide Precipitation Composites Supporting Rainfall- Induced Flash Flood Emergency Management 105
Shinju Park, Marc Berenguer, Daniel Sempere- Torres, and Annakaisa Von Lerber
5.1 Introduction 105
5.2 The EUMETNET OPERA Radar Precipitation Composites 106
5.3 Monitoring the Quality of the Opera Precipitation Composites 108
5.4 Application of Opera Precipitation Composites for Flash Flood Hazard Nowcasting 110
5.5 Conclusions and Outlook 113
References 116
6 Towards Impact- Based Communication During Climate Emergencies: A Community- Based Approach to Improve Flood Early Warning Systems 119
Erika Meléndez- Landaverde, Daniel Sempere- Torres, and Shinju Park
6.1 Introduction 119
6.2 Impact- Based Early Warning Systems (IB- EWS) for Actionable Decisions: Key Aspects 121
6.2.1 Partnerships for an Effective Co- Design IB- EWS 122
6.2.2 End Users: Identifying Needs for Emergency Response 123
6.2.3 Risk Identification and Impact Data Collection 124
6.2.4 Evaluation of IB- EWSs 125
6.3 The Next Step for Community- Based EWS: The Site- Specific EWS Framework (SS- EWS) 125
6.3.1 The Site- Specific Early Warning System Framework (SS- EWS) 126
6.4 The SS- EWS in Catalonia, NE Spain: Experiences and Lessons Learned 128
6.4.1 Community- Based Sessions in Terrassa: The Co- Design Process and Experiences 129
6.4.2 Community- Based Emergency Response: SS- EWS Real- Time Application in Terrassa 132
6.4.3 The Site- Specific Warnings (SSWs): Their Influence on the Risk Perception and Understanding of Users in Blanes 132
6.4.4 A4alerts: Mobile Application for Emergency Communication 134
6.5 An Outlook on Future Community and Impact- Based Communication Tools for Floods 135
Notes 137
References 137
7 Challenges for a Better Use of Crowdsourcing Information in Climate Emergency Situational Awareness and Early Warning Systems 141
Milan Kalas, Joy Ommer, Amin Shakya, Sasa Vraníc, Denys Kolokol, and Tommaso Sabattini
7.1 Introduction 141
7.2 Crowd- Generated Content to Support Emergency Management and Early Warning 143
7.2.1 Examples of the Citizen Science in Disaster Risk Management 143
7.2.2 Tools 144
7.2.3 Challenges in the Integration and Application of Citizen- Generated Content in DRM 145
7.3 ANYWHERE Applications and Their Lessons Learnt 146
7.3.1 Crowd Mapping to Support Real- Time Risk Assessment 147
7.3.2 Social Media Streaming to Increase Emergency Situational Awareness 147
7.3.3 A Crowdsourcing Solution for Collecting Information on the Magnitude and Impact of Disasters 153
7.3.4 Towards a Holistic System 155
7.3.5 Facilitating Communication Between Actors in Emergency Management 157
7.4 Conclusion 158
Note 159
References 159
8 Co- Evaluation: How to Measure Achievements in Complex Co- Production Projects? ANYWHERE's Contribution to Enhance Emergency Management of Weather and Climate Events 163
Oliver Gebhardt and Christian Kuhlicke
8.1 Introduction 163
8.2 Application of the ANYWHERE Co- Evaluation Framework 165
8.2.1 Step 1: Context Analysis 166
8.2.2 Step 2: Description of Baseline Scenario and ANYWHERE Scenario 166
8.2.3 Step 3: Selection of Suitable and Feasible Criteria 166
8.2.4 Step 4: Selection of Appropriate Co- Evaluation Method 167
8.2.5 Step 5: Data Collection 167
8.2.6 Step 6: Data Aggregation and Analysis 168
8.3 Discussion of Co- Evaluation Results 168
8.4 Discussion 176
8.5 Conclusion 177
Notes 177
References 178
9 Using Artificial Intelligence to Manage Extreme Weather Events: The Impact of the beAWARE Solution 181
Anastasios Karakostas, Stefanos Vrochidis, and Ioannis Kompatsiaris
9.1 Introduction 181
9.2 Overall Objectives of the Project 182
9.3 The Impact of beAWARE 188
9.3.1 Scientific and Innovation Impact 188
9.3.2 Economic Impact 191
9.3.3 Safety Impact 191
9.3.4 Training Impact 191
9.3.5 Policymakers 193
9.3.6 First Responders 194
9.3.7 General Public (Citizens) 195
9.4 Conclusion 196
Acknowledgement 197
References 197
10 Innovative Visual Analysis Solutions to Support Disaster Management 199
Emmanouil Michail, Panagiotis Giannakeris, Ilias Koulalis, Stefanos Vrochidis, and Ioannis Kompatsiaris
10.1 Introduction 199
10.2 Related Work 200
10.3 Methodology 203
10.3.1 Disaster Detection 204
10.3.2 Object Detection 205
10.3.3 River Level Monitoring 206
10.3.4 Drone Analysis 206
10.3.5 Traffic Analysis and Management 209
10.4 System Evaluation 211
10.4.1 Disaster Detection 212
10.4.2 Object Detection and Tracking 213
10.4.3 River Level Monitoring 215
10.4.4 Drone Analysis 217
10.4.5 Traffic Analysis and Management 219
10.5 Conclusions 221
References 221
11 Social Media Monitoring for Disaster Management 224
Stelios Andreadis, Ilias Gialampoukidis, Stefanos Vrochidis, and Ioannis Kompatsiaris
11.1 Introduction 224
11.2 Social Media Analysis 225
11.2.1 Framework Overview 225
11.2.2 Data Collection from Twitter 226
11.2.3 Analysis of Social Media Data 227
11.2.4 Data Representation 232
11.3 Social Media Clustering 234
11.3.1 Evaluation of Spatial Clustering Techniques 234
11.3.2 The Proposed Spatiotemporal Clustering 236
11.4 Visualizations 237
11.4.1 Annotation Tool 237
11.4.2 Demonstration Tool 239
11.5 Conclusion 240
Notes 241
References 241
12 Human- Centred Public Warnings 243
Claudio Rossi and Antonella Frisiello
12.1 Introduction 243
12.2 Risk Communication 245
12.2.1 Risk Communication Key Aspects 246
12.2.2 United Nation Guidelines 249
12.3 Technical Standards and Recommendations 250
12.3.1 Standards and Requirements for Public Warning Systems Implementation 250
12.3.2 The Common Alerting Protocol 251
12.3.3 Recommended System Architecture 252
12.3.4 Use of Technical Standards 257
12.3.5 Media Adaptation and Usability of Alerts 260
12.4 Future Outlooks in Public Warning and Risk Communication 267
12.4.1 Crowdsourcing Approaches 267
12.4.2 Organizational Best Practices 269
Note 271
References 272
13 A DRM Solution for Professionals and Citizens 275
Claudio Rossi, Antonella Frisiello, Gianluca Marucco, and Marco Pini
13.1 A Novel Mobile Application for DRR 275
13.2 The I- REACT Co- Design Approach 276
13.2.1 The Co- Design Process in the I- REACT Project 277
13.2.2 From Data to Specifications: The Results of I- REACT Co- Design Activities 280
13.3 The Development and Implementation of the I- REACT Mobile Solution 285
13.4 Gamified Crowdsourcing for Disaster Risk Management 290
13.5 The I- REACT Wearable Solution for First Responders 293
13.5.1 Ad- hoc Positioning Wearable Device for Enhanced Localization 294
13.5.2 Operational Scenario 295
13.5.3 Device Operating Modes 297
13.5.4 Communication Flow 299
13.5.5 Wearable Device Implementation and Prototyping Cycles 299
13.5.6 Wearable Device Performance Validation 301
13.6 Improved Positioning of First Responders Using EGNSS Technologies 302
13.6.1 A Service- Oriented Cloud- Based Architecture for Mobile Geolocated Emergency Services (EGNOS in the Cloud) 304
13.6.2 EDAS Service Selector, Decoder and Storage 306
13.6.3 Augmented PVT and Integrity Computation 307
13.6.4 Implementation of the Architecture of the Cloud Software Module 308
13.6.5 Performance Evaluation of the Implementation 309
13.6.6 Positioning Integrity Computation for Consumer- Grade GNSS Receivers 313
References 323
14 Transforming Data Coming from Social Media Streams into Disaster- Related Information 326
Claudio Rossi, Edoardo Arnaudo, Dario Salza, Giacomo Blanco, and Lorenzo Bongiovanni
14.1 Introduction 326
14.2 Natural Language Processing Methods for Emergency- Related Text Processing 331
14.2.1 Document Representation 332
14.2.2 Document Classification 333
14.2.3 Named Entity Recognition 334
14.3 Model Architecture 335
14.4 Classification Results 336
14.4.1 Bag of Words with SVM 336
14.4.2 CNN with Multilingual Word Embeddings 337
14.4.3 CNN with XML- T Contextual Word Embeddings 338
14.5 Image Filtering and Classification for Contextual Awareness 339
14.5.1 Filtering Unwanted Images 339
14.5.2 Methodology for NSFW Classification 340
14.5.3 Classifying Relevant Images 341
14.5.4 Methodology for Image Classification 343
14.6 Event Detection 345
14.6.1 Related Work 346
14.6.2 Methodology 349
14.6.3 Evaluation of the Event Detection Pipeline 351
14.7 Impact Extraction 354
14.7.1 Related Work 354
14.7.2 Methodology 356
14.7.3 Aggregating the Information 357
14.7.4 Evaluation Results 358
14.8 Annex 1: Definition of Yara Rules for Impact Estimation 360
Funding 362
Notes 362
References 362
15 Conclusions and Perspectives 368
Philippe Quevauviller
15.1 Introduction 368
15.2 Policy Background 369
15.2.1 Civil Protection Policies 370
15.2.2 EU Strategy on Adaptation to Climate Change 372
15.2.3 Water Framework and Marine Policies 373
15.2.4 Links with Projects Subject to this Book 374
15.3 Actor's Interactions and Community Building 375
15.3.1 Who are the Actors? 375
15.3.2 Community Building 377
15.4 Research Trends Related to Disaster Risks (Including Climate Extremes) in the Security Research Area 379
15.4.1 Societal Resilience 379
15.4.2 Tools for Integrated Risk Reduction for Extreme Climate Events 381
15.5 Conclusions, Gaps and Recommendations 383
Notes 384
References 384
Index 386
Daniel Sempere-Torres is Professor at Universitat Politècnica de Catalunya, Barcelona, Spain.
Anastasios Karakostas is Director at DRAXIS Environmental S.A. and former Senior Researcher at the Centre for Research and Technology Hellas, Thessaloniki, Greece.
Claudio Rossi is Program Manager and Senior Researcher at LINKS Foundation, Turin, Italy.
Philippe Quevauviller is Former Professor at Vrije Universiteit Brussel, Brussels, Belgium and Research Programming and Policy Officer at the European Commission.
Anastasios Karakostas is Director at DRAXIS Environmental S.A. and former Senior Researcher at the Centre for Research and Technology Hellas, Thessaloniki, Greece.
Claudio Rossi is Program Manager and Senior Researcher at LINKS Foundation, Turin, Italy.
Philippe Quevauviller is Former Professor at Vrije Universiteit Brussel, Brussels, Belgium and Research Programming and Policy Officer at the European Commission.
