{"product_id":"responding-to-extreme-weather-events-isbn-9781119741589","title":"Responding to Extreme Weather Events","description":"\u003cp\u003e \u003cb\u003eAn up-to-date discussion of the latest in weather-related event forecasting and management\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e In \u003ci\u003eResponding to Extreme Weather Events\u003c\/i\u003e, 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. \u003c\/p\u003e\u003cp\u003eThe authors cover the entire crisis management cycle, from awareness and early warning to effective responses to extreme weather events. Readers will also find:  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA thorough introduction to the science and policy background of managing extreme weather events \u003c\/li\u003e\n\u003cli\u003eComprehensive explorations of impact forecasting for extreme weather events, including discussion of the ANYWHERE project \u003c\/li\u003e\n\u003cli\u003ePractical discussions of how to improve resilience to weather-related emergencies with advanced cyber technologies, including discussion of the I-REACT project \u003c\/li\u003e\n\u003cli\u003eA novel framework for crisis management during extreme weather events, including discussion of the BeAWARE project\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eEssential for disaster management professionals, \u003ci\u003eResponding to Extreme Weather Events \u003c\/i\u003ewill also benefit academic staff and researchers with an interest in extreme weather events and their consequences. \u003c\/p\u003e\u003cp\u003eList of Contributors xii\u003c\/p\u003e \u003cp\u003eSeries Preface xvi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 The ANYWHERE Paradigm Shift in Responding to Weather and Climate Emergencies: Impact Forecasting, Dynamic Vulnerability and the Need for Citizen's Involvement 1\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDaniel Sempere- Torres and Marc Berenguer\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Disaster Risk Management in Times of Climate Change: The Need of a Proactive Approach 1\u003c\/p\u003e \u003cp\u003e1.2 Adapting Risk Management to the 'New Normality': The Case of Flood Risk Management 2\u003c\/p\u003e \u003cp\u003e1.3 Changing the Paradigm: Impact- Based Multi- Hazard Early Warning Systems to Move from Reactive to Pro- Active Emergency Response Strategies 4\u003c\/p\u003e \u003cp\u003e1.3.1 From Reactive to Proactive Emergency Response Strategies 5\u003c\/p\u003e \u003cp\u003e1.3.2 The ANYWHERE MH- IEWS 9\u003c\/p\u003e \u003cp\u003e1.4 The New Paradigm: Dynamic Vulnerability 13\u003c\/p\u003e \u003cp\u003e1.5 Future Work: From Multi- Hazards to Multi- Risk IEWS 16\u003c\/p\u003e \u003cp\u003eNotes 17\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Hydrometeorological Drought Forecasts: Lessons Learned from ANYWHERE and Next Steps to Improve Drought Management 23\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSamuel J. Sutanto and Henny A.J. Van Lanen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 23\u003c\/p\u003e \u003cp\u003e2.2 Method for Forecasting Hydrometeorological Droughts 25\u003c\/p\u003e \u003cp\u003e2.2.1 The Climate (ECMWF SEAS5) and Hydrological (LISFLOOD) Models 25\u003c\/p\u003e \u003cp\u003e2.2.2 The Drought Indices 26\u003c\/p\u003e \u003cp\u003e2.2.3 The Drought Forecast Algorithms 28\u003c\/p\u003e \u003cp\u003e2.3 Hydrometeorological Drought Forecasts 30\u003c\/p\u003e \u003cp\u003e2.3.1 Meteorological Drought Forecasts 30\u003c\/p\u003e \u003cp\u003e2.3.2 Hydrological Drought Forecasts 31\u003c\/p\u003e \u003cp\u003e2.4 Drought Forecast Performance 33\u003c\/p\u003e \u003cp\u003e2.4.1 The Origin of Seasonal Drought Forecast Skill 33\u003c\/p\u003e \u003cp\u003e2.4.2 Examples of Assessment of Seasonal Drought Forecast Performance 34\u003c\/p\u003e \u003cp\u003e2.5 Importance of Catchment Memory 38\u003c\/p\u003e \u003cp\u003e2.6 Outlook and Future Improvements 40\u003c\/p\u003e \u003cp\u003e2.6.1 Drought Impact Forecasts 41\u003c\/p\u003e \u003cp\u003e2.6.2 Compound and Cascading (CC) Dry Hazards 43\u003c\/p\u003e \u003cp\u003eReferences 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Experiences and Lessons Learnt in Wildfire Management with PROPAGATOR, an Operational Cellular- Automata- Based Wildfire Simulator 49\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAndrea Trucchia, Mirko D'Andrea, Francesco Baghino, Nicolò Perello, Nicola Rebora, and Paolo Fiorucci\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 49\u003c\/p\u003e \u003cp\u003e3.1.1 Mathematical Models for Wildfire Management 50\u003c\/p\u003e \u003cp\u003e3.2 Synopsis of Propagator Development: More than a Decade of Wildfire Simulations 52\u003c\/p\u003e \u003cp\u003e3.3 Propagator Model 55\u003c\/p\u003e \u003cp\u003e3.4 Case Studies 62\u003c\/p\u003e \u003cp\u003e3.4.1 Data Retrieval 62\u003c\/p\u003e \u003cp\u003e3.5 Results and Discussion 65\u003c\/p\u003e \u003cp\u003e3.5.1 Performance Indicators 65\u003c\/p\u003e \u003cp\u003e3.5.2 Performances of Test Cases 70\u003c\/p\u003e \u003cp\u003e3.5.3 An Example of Continuous Improvement and Operational Deployment: Implementation in Ireland 71\u003c\/p\u003e \u003cp\u003e3.6 Conclusions 71\u003c\/p\u003e \u003cp\u003eReferences 73\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Building an Operational Decision Support System for Multiple Weather- Induced Health Hazards: ANYWHERE Developments and Future Applications 77\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eClaudia Di Napoli\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 77\u003c\/p\u003e \u003cp\u003e4.2 Heatwave Prediction in ANYWHERE 79\u003c\/p\u003e \u003cp\u003e4.2.1 The Universal Thermal Climate Index 80\u003c\/p\u003e \u003cp\u003e4.2.2 Forecasting Algorithms 80\u003c\/p\u003e \u003cp\u003e4.2.3 Heatwave Products 81\u003c\/p\u003e \u003cp\u003e4.2.4 Integration in the MH- EWS 81\u003c\/p\u003e \u003cp\u003e4.2.5 Temperature Products 81\u003c\/p\u003e \u003cp\u003e4.3 Air Pollution Prediction in ANYWHERE 83\u003c\/p\u003e \u003cp\u003e4.3.1 Air Quality 83\u003c\/p\u003e \u003cp\u003e4.3.2 Forecasting Algorithms 85\u003c\/p\u003e \u003cp\u003e4.3.3 Air Quality Products 85\u003c\/p\u003e \u003cp\u003e4.3.4 Integration in the MH- EWS 85\u003c\/p\u003e \u003cp\u003e4.4 ANYWHERE MH- EWS in Action: The European 2017 Heatwave 86\u003c\/p\u003e \u003cp\u003e4.5 Implementation at Pilot Sites 87\u003c\/p\u003e \u003cp\u003e4.5.1 Integration of Local Heatwave and Air Pollution Products 90\u003c\/p\u003e \u003cp\u003e4.5.2 Evaluation at Pilot Sites 92\u003c\/p\u003e \u003cp\u003e4.6 Future Applications 93\u003c\/p\u003e \u003cp\u003e4.6.1 Impact- Based Warnings 93\u003c\/p\u003e \u003cp\u003e4.6.2 Multi- Hazard Forecasting 95\u003c\/p\u003e \u003cp\u003e4.6.3 Cold Spells as a Health Hazard 97\u003c\/p\u003e \u003cp\u003e4.6.4 Social Sensing 97\u003c\/p\u003e \u003cp\u003e4.6.5 Protecting the Vulnerable 98\u003c\/p\u003e \u003cp\u003e4.7 Conclusions 98\u003c\/p\u003e \u003cp\u003eFunding 99\u003c\/p\u003e \u003cp\u003eAcknowledgements 99\u003c\/p\u003e \u003cp\u003eNotes 99\u003c\/p\u003e \u003cp\u003eReferences 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 The EUMETNET OPERA Radar Network – European- Wide Precipitation Composites Supporting Rainfall- Induced Flash Flood Emergency Management 105\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eShinju Park, Marc Berenguer, Daniel Sempere- Torres, and Annakaisa Von Lerber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 105\u003c\/p\u003e \u003cp\u003e5.2 The EUMETNET OPERA Radar Precipitation Composites 106\u003c\/p\u003e \u003cp\u003e5.3 Monitoring the Quality of the Opera Precipitation Composites 108\u003c\/p\u003e \u003cp\u003e5.4 Application of Opera Precipitation Composites for Flash Flood Hazard Nowcasting 110\u003c\/p\u003e \u003cp\u003e5.5 Conclusions and Outlook 113\u003c\/p\u003e \u003cp\u003eReferences 116\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Towards Impact- Based Communication During Climate Emergencies: A Community- Based Approach to Improve Flood Early Warning Systems 119\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eErika Meléndez- Landaverde, Daniel Sempere- Torres, and Shinju Park\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 119\u003c\/p\u003e \u003cp\u003e6.2 Impact- Based Early Warning Systems (IB- EWS) for Actionable Decisions: Key Aspects 121\u003c\/p\u003e \u003cp\u003e6.2.1 Partnerships for an Effective Co- Design IB- EWS 122\u003c\/p\u003e \u003cp\u003e6.2.2 End Users: Identifying Needs for Emergency Response 123\u003c\/p\u003e \u003cp\u003e6.2.3 Risk Identification and Impact Data Collection 124\u003c\/p\u003e \u003cp\u003e6.2.4 Evaluation of IB- EWSs 125\u003c\/p\u003e \u003cp\u003e6.3 The Next Step for Community- Based EWS: The Site- Specific EWS Framework (SS- EWS) 125\u003c\/p\u003e \u003cp\u003e6.3.1 The Site- Specific Early Warning System Framework (SS- EWS) 126\u003c\/p\u003e \u003cp\u003e6.4 The SS- EWS in Catalonia, NE Spain: Experiences and Lessons Learned 128\u003c\/p\u003e \u003cp\u003e6.4.1 Community- Based Sessions in Terrassa: The Co- Design Process and Experiences 129\u003c\/p\u003e \u003cp\u003e6.4.2 Community- Based Emergency Response: SS- EWS Real- Time Application in Terrassa 132\u003c\/p\u003e \u003cp\u003e6.4.3 The Site- Specific Warnings (SSWs): Their Influence on the Risk Perception and Understanding of Users in Blanes 132\u003c\/p\u003e \u003cp\u003e6.4.4 A4alerts: Mobile Application for Emergency Communication 134\u003c\/p\u003e \u003cp\u003e6.5 An Outlook on Future Community and Impact- Based Communication Tools for Floods 135\u003c\/p\u003e \u003cp\u003eNotes 137\u003c\/p\u003e \u003cp\u003eReferences 137\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Challenges for a Better Use of Crowdsourcing Information in Climate Emergency Situational Awareness and Early Warning Systems 141\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMilan Kalas, Joy Ommer, Amin Shakya, Saša Vraníc, Denys Kolokol, and Tommaso Sabattini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 141\u003c\/p\u003e \u003cp\u003e7.2 Crowd- Generated Content to Support Emergency Management and Early Warning 143\u003c\/p\u003e \u003cp\u003e7.2.1 Examples of the Citizen Science in Disaster Risk Management 143\u003c\/p\u003e \u003cp\u003e7.2.2 Tools 144\u003c\/p\u003e \u003cp\u003e7.2.3 Challenges in the Integration and Application of Citizen- Generated Content in DRM 145\u003c\/p\u003e \u003cp\u003e7.3 ANYWHERE Applications and Their Lessons Learnt 146\u003c\/p\u003e \u003cp\u003e7.3.1 Crowd Mapping to Support Real- Time Risk Assessment 147\u003c\/p\u003e \u003cp\u003e7.3.2 Social Media Streaming to Increase Emergency Situational Awareness 147\u003c\/p\u003e \u003cp\u003e7.3.3 A Crowdsourcing Solution for Collecting Information on the Magnitude and Impact of Disasters 153\u003c\/p\u003e \u003cp\u003e7.3.4 Towards a Holistic System 155\u003c\/p\u003e \u003cp\u003e7.3.5 Facilitating Communication Between Actors in Emergency Management 157\u003c\/p\u003e \u003cp\u003e7.4 Conclusion 158\u003c\/p\u003e \u003cp\u003eNote 159\u003c\/p\u003e \u003cp\u003eReferences 159\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Co- Evaluation: How to Measure Achievements in Complex Co- Production Projects? ANYWHERE's Contribution to Enhance Emergency Management of Weather and Climate Events 163\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eOliver Gebhardt and Christian Kuhlicke\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 163\u003c\/p\u003e \u003cp\u003e8.2 Application of the ANYWHERE Co- Evaluation Framework 165\u003c\/p\u003e \u003cp\u003e8.2.1 Step 1: Context Analysis 166\u003c\/p\u003e \u003cp\u003e8.2.2 Step 2: Description of Baseline Scenario and ANYWHERE Scenario 166\u003c\/p\u003e \u003cp\u003e8.2.3 Step 3: Selection of Suitable and Feasible Criteria 166\u003c\/p\u003e \u003cp\u003e8.2.4 Step 4: Selection of Appropriate Co- Evaluation Method 167\u003c\/p\u003e \u003cp\u003e8.2.5 Step 5: Data Collection 167\u003c\/p\u003e \u003cp\u003e8.2.6 Step 6: Data Aggregation and Analysis 168\u003c\/p\u003e \u003cp\u003e8.3 Discussion of Co- Evaluation Results 168\u003c\/p\u003e \u003cp\u003e8.4 Discussion 176\u003c\/p\u003e \u003cp\u003e8.5 Conclusion 177\u003c\/p\u003e \u003cp\u003eNotes 177\u003c\/p\u003e \u003cp\u003eReferences 178\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Using Artificial Intelligence to Manage Extreme Weather Events: The Impact of the beAWARE Solution 181\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eAnastasios Karakostas, Stefanos Vrochidis, and Ioannis Kompatsiaris\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 181\u003c\/p\u003e \u003cp\u003e9.2 Overall Objectives of the Project 182\u003c\/p\u003e \u003cp\u003e9.3 The Impact of beAWARE 188\u003c\/p\u003e \u003cp\u003e9.3.1 Scientific and Innovation Impact 188\u003c\/p\u003e \u003cp\u003e9.3.2 Economic Impact 191\u003c\/p\u003e \u003cp\u003e9.3.3 Safety Impact 191\u003c\/p\u003e \u003cp\u003e9.3.4 Training Impact 191\u003c\/p\u003e \u003cp\u003e9.3.5 Policymakers 193\u003c\/p\u003e \u003cp\u003e9.3.6 First Responders 194\u003c\/p\u003e \u003cp\u003e9.3.7 General Public (Citizens) 195\u003c\/p\u003e \u003cp\u003e9.4 Conclusion 196\u003c\/p\u003e \u003cp\u003eAcknowledgement 197\u003c\/p\u003e \u003cp\u003eReferences 197\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Innovative Visual Analysis Solutions to Support Disaster Management 199\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eEmmanouil Michail, Panagiotis Giannakeris, Ilias Koulalis, Stefanos Vrochidis, and Ioannis Kompatsiaris\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 199\u003c\/p\u003e \u003cp\u003e10.2 Related Work 200\u003c\/p\u003e \u003cp\u003e10.3 Methodology 203\u003c\/p\u003e \u003cp\u003e10.3.1 Disaster Detection 204\u003c\/p\u003e \u003cp\u003e10.3.2 Object Detection 205\u003c\/p\u003e \u003cp\u003e10.3.3 River Level Monitoring 206\u003c\/p\u003e \u003cp\u003e10.3.4 Drone Analysis 206\u003c\/p\u003e \u003cp\u003e10.3.5 Traffic Analysis and Management 209\u003c\/p\u003e \u003cp\u003e10.4 System Evaluation 211\u003c\/p\u003e \u003cp\u003e10.4.1 Disaster Detection 212\u003c\/p\u003e \u003cp\u003e10.4.2 Object Detection and Tracking 213\u003c\/p\u003e \u003cp\u003e10.4.3 River Level Monitoring 215\u003c\/p\u003e \u003cp\u003e10.4.4 Drone Analysis 217\u003c\/p\u003e \u003cp\u003e10.4.5 Traffic Analysis and Management 219\u003c\/p\u003e \u003cp\u003e10.5 Conclusions 221\u003c\/p\u003e \u003cp\u003eReferences 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Social Media Monitoring for Disaster Management 224\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eStelios Andreadis, Ilias Gialampoukidis, Stefanos Vrochidis, and Ioannis Kompatsiaris\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 224\u003c\/p\u003e \u003cp\u003e11.2 Social Media Analysis 225\u003c\/p\u003e \u003cp\u003e11.2.1 Framework Overview 225\u003c\/p\u003e \u003cp\u003e11.2.2 Data Collection from Twitter 226\u003c\/p\u003e \u003cp\u003e11.2.3 Analysis of Social Media Data 227\u003c\/p\u003e \u003cp\u003e11.2.4 Data Representation 232\u003c\/p\u003e \u003cp\u003e11.3 Social Media Clustering 234\u003c\/p\u003e \u003cp\u003e11.3.1 Evaluation of Spatial Clustering Techniques 234\u003c\/p\u003e \u003cp\u003e11.3.2 The Proposed Spatiotemporal Clustering 236\u003c\/p\u003e \u003cp\u003e11.4 Visualizations 237\u003c\/p\u003e \u003cp\u003e11.4.1 Annotation Tool 237\u003c\/p\u003e \u003cp\u003e11.4.2 Demonstration Tool 239\u003c\/p\u003e \u003cp\u003e11.5 Conclusion 240\u003c\/p\u003e \u003cp\u003eNotes 241\u003c\/p\u003e \u003cp\u003eReferences 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Human- Centred Public Warnings 243\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eClaudio Rossi and Antonella Frisiello\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 243\u003c\/p\u003e \u003cp\u003e12.2 Risk Communication 245\u003c\/p\u003e \u003cp\u003e12.2.1 Risk Communication Key Aspects 246\u003c\/p\u003e \u003cp\u003e12.2.2 United Nation Guidelines 249\u003c\/p\u003e \u003cp\u003e12.3 Technical Standards and Recommendations 250\u003c\/p\u003e \u003cp\u003e12.3.1 Standards and Requirements for Public Warning Systems Implementation 250\u003c\/p\u003e \u003cp\u003e12.3.2 The Common Alerting Protocol 251\u003c\/p\u003e \u003cp\u003e12.3.3 Recommended System Architecture 252\u003c\/p\u003e \u003cp\u003e12.3.4 Use of Technical Standards 257\u003c\/p\u003e \u003cp\u003e12.3.5 Media Adaptation and Usability of Alerts 260\u003c\/p\u003e \u003cp\u003e12.4 Future Outlooks in Public Warning and Risk Communication 267\u003c\/p\u003e \u003cp\u003e12.4.1 Crowdsourcing Approaches 267\u003c\/p\u003e \u003cp\u003e12.4.2 Organizational Best Practices 269\u003c\/p\u003e \u003cp\u003eNote 271\u003c\/p\u003e \u003cp\u003eReferences 272\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 A DRM Solution for Professionals and Citizens 275\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eClaudio Rossi, Antonella Frisiello, Gianluca Marucco, and Marco Pini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 A Novel Mobile Application for DRR 275\u003c\/p\u003e \u003cp\u003e13.2 The I- REACT Co- Design Approach 276\u003c\/p\u003e \u003cp\u003e13.2.1 The Co- Design Process in the I- REACT Project 277\u003c\/p\u003e \u003cp\u003e13.2.2 From Data to Specifications: The Results of I- REACT Co- Design Activities 280\u003c\/p\u003e \u003cp\u003e13.3 The Development and Implementation of the I- REACT Mobile Solution 285\u003c\/p\u003e \u003cp\u003e13.4 Gamified Crowdsourcing for Disaster Risk Management 290\u003c\/p\u003e \u003cp\u003e13.5 The I- REACT Wearable Solution for First Responders 293\u003c\/p\u003e \u003cp\u003e13.5.1 Ad- hoc Positioning Wearable Device for Enhanced Localization 294\u003c\/p\u003e \u003cp\u003e13.5.2 Operational Scenario 295\u003c\/p\u003e \u003cp\u003e13.5.3 Device Operating Modes 297\u003c\/p\u003e \u003cp\u003e13.5.4 Communication Flow 299\u003c\/p\u003e \u003cp\u003e13.5.5 Wearable Device Implementation and Prototyping Cycles 299\u003c\/p\u003e \u003cp\u003e13.5.6 Wearable Device Performance Validation 301\u003c\/p\u003e \u003cp\u003e13.6 Improved Positioning of First Responders Using EGNSS Technologies 302\u003c\/p\u003e \u003cp\u003e13.6.1 A Service- Oriented Cloud- Based Architecture for Mobile Geolocated Emergency Services (EGNOS in the Cloud) 304\u003c\/p\u003e \u003cp\u003e13.6.2 EDAS Service Selector, Decoder and Storage 306\u003c\/p\u003e \u003cp\u003e13.6.3 Augmented PVT and Integrity Computation 307\u003c\/p\u003e \u003cp\u003e13.6.4 Implementation of the Architecture of the Cloud Software Module 308\u003c\/p\u003e \u003cp\u003e13.6.5 Performance Evaluation of the Implementation 309\u003c\/p\u003e \u003cp\u003e13.6.6 Positioning Integrity Computation for Consumer- Grade GNSS Receivers 313\u003c\/p\u003e \u003cp\u003eReferences 323\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Transforming Data Coming from Social Media Streams into Disaster- Related Information 326\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eClaudio Rossi, Edoardo Arnaudo, Dario Salza, Giacomo Blanco, and Lorenzo Bongiovanni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 326\u003c\/p\u003e \u003cp\u003e14.2 Natural Language Processing Methods for Emergency- Related Text Processing 331\u003c\/p\u003e \u003cp\u003e14.2.1 Document Representation 332\u003c\/p\u003e \u003cp\u003e14.2.2 Document Classification 333\u003c\/p\u003e \u003cp\u003e14.2.3 Named Entity Recognition 334\u003c\/p\u003e \u003cp\u003e14.3 Model Architecture 335\u003c\/p\u003e \u003cp\u003e14.4 Classification Results 336\u003c\/p\u003e \u003cp\u003e14.4.1 Bag of Words with SVM 336\u003c\/p\u003e \u003cp\u003e14.4.2 CNN with Multilingual Word Embeddings 337\u003c\/p\u003e \u003cp\u003e14.4.3 CNN with XML- T Contextual Word Embeddings 338\u003c\/p\u003e \u003cp\u003e14.5 Image Filtering and Classification for Contextual Awareness 339\u003c\/p\u003e \u003cp\u003e14.5.1 Filtering Unwanted Images 339\u003c\/p\u003e \u003cp\u003e14.5.2 Methodology for NSFW Classification 340\u003c\/p\u003e \u003cp\u003e14.5.3 Classifying Relevant Images 341\u003c\/p\u003e \u003cp\u003e14.5.4 Methodology for Image Classification 343\u003c\/p\u003e \u003cp\u003e14.6 Event Detection 345\u003c\/p\u003e \u003cp\u003e14.6.1 Related Work 346\u003c\/p\u003e \u003cp\u003e14.6.2 Methodology 349\u003c\/p\u003e \u003cp\u003e14.6.3 Evaluation of the Event Detection Pipeline 351\u003c\/p\u003e \u003cp\u003e14.7 Impact Extraction 354\u003c\/p\u003e \u003cp\u003e14.7.1 Related Work 354\u003c\/p\u003e \u003cp\u003e14.7.2 Methodology 356\u003c\/p\u003e \u003cp\u003e14.7.3 Aggregating the Information 357\u003c\/p\u003e \u003cp\u003e14.7.4 Evaluation Results 358\u003c\/p\u003e \u003cp\u003e14.8 Annex 1: Definition of Yara Rules for Impact Estimation 360\u003c\/p\u003e \u003cp\u003eFunding 362\u003c\/p\u003e \u003cp\u003eNotes 362\u003c\/p\u003e \u003cp\u003eReferences 362\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Conclusions and Perspectives 368\u003cbr\u003e\u003c\/b\u003e\u003ci\u003ePhilippe Quevauviller\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 368\u003c\/p\u003e \u003cp\u003e15.2 Policy Background 369\u003c\/p\u003e \u003cp\u003e15.2.1 Civil Protection Policies 370\u003c\/p\u003e \u003cp\u003e15.2.2 EU Strategy on Adaptation to Climate Change 372\u003c\/p\u003e \u003cp\u003e15.2.3 Water Framework and Marine Policies 373\u003c\/p\u003e \u003cp\u003e15.2.4 Links with Projects Subject to this Book 374\u003c\/p\u003e \u003cp\u003e15.3 Actor's Interactions and Community Building 375\u003c\/p\u003e \u003cp\u003e15.3.1 Who are the Actors? 375\u003c\/p\u003e \u003cp\u003e15.3.2 Community Building 377\u003c\/p\u003e \u003cp\u003e15.4 Research Trends Related to Disaster Risks (Including Climate Extremes) in the Security Research Area 379\u003c\/p\u003e \u003cp\u003e15.4.1 Societal Resilience 379\u003c\/p\u003e \u003cp\u003e15.4.2 Tools for Integrated Risk Reduction for Extreme Climate Events 381\u003c\/p\u003e \u003cp\u003e15.5 Conclusions, Gaps and Recommendations 383\u003c\/p\u003e \u003cp\u003eNotes 384\u003c\/p\u003e \u003cp\u003eReferences 384\u003c\/p\u003e \u003cp\u003eIndex 386\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eDaniel Sempere-Torres \u003c\/b\u003eis Professor at Universitat Politècnica de Catalunya, Barcelona, Spain. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAnastasios Karakostas \u003c\/b\u003eis Director at DRAXIS Environmental S.A. and former Senior Researcher at the Centre for Research and Technology Hellas, Thessaloniki, Greece. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eClaudio Rossi \u003c\/b\u003eis Program Manager and Senior Researcher at LINKS Foundation, Turin, Italy. \u003c\/p\u003e\u003cp\u003e\u003cb\u003ePhilippe Quevauviller \u003c\/b\u003eis Former Professor at Vrije Universiteit Brussel, Brussels, Belgium and Research Programming and Policy Officer at the European Commission.   \u003c\/p\u003e\u003cp\u003e \u003cb\u003eAn up-to-date discussion of the latest in weather-related event forecasting and management\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e In \u003ci\u003eResponding to Extreme Weather Events\u003c\/i\u003e, 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. \u003c\/p\u003e\u003cp\u003eThe authors cover the entire crisis management cycle, from awareness and early warning to effective responses to extreme weather events. Readers will also find:  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA thorough introduction to the science and policy background of managing extreme weather events \u003c\/li\u003e\n\u003cli\u003eComprehensive explorations of impact forecasting for extreme weather events, including discussion of the ANYWHERE project \u003c\/li\u003e\n\u003cli\u003ePractical discussions of how to improve resilience to weather-related emergencies with advanced cyber technologies, including discussion of the I-REACT project \u003c\/li\u003e\n\u003cli\u003eA novel framework for crisis management during extreme weather events, including discussion of the BeAWARE project\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eEssential for disaster management professionals, \u003ci\u003eResponding to Extreme Weather Events \u003c\/i\u003ewill also benefit academic staff and researchers with an interest in extreme weather events and their consequences.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989951267045,"sku":"NP9781119741589","price":170.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119741589.jpg?v=1761786013","url":"https:\/\/k12savings.com\/products\/responding-to-extreme-weather-events-isbn-9781119741589","provider":"K12savings","version":"1.0","type":"link"}