Description
A holistic view of geospatial data and analysis across the risk management lifecycle
Geospatial data and analytical tools are widely used for disaster management, insurance, humanitarian response, and defence—yet methodologies remain siloed. Geographic Perspectives on Disaster Risk Management, written by a team of experienced practitioners in catastrophe risk analytics and geospatial studies, connects these sectors by comparing approaches, identifying common challenges, and distilling cross-sector best practices for preparation, response, recovery, and mitigation.
Structured around the disaster risk cycle, the book addresses exposure and vulnerability mapping, risk preparedness and mitigation strategies, event monitoring, damage assessment, resilience building, and risk communication. It draws on data sources ranging from local traffic cameras to geostationary satellites and includes case studies illustrating real-world applications alongside outcome-based evaluations of current practices and future developments in disaster risk assessment.
Readers will also find:
- Cross-sector comparison of methodologies from international development, emergency response, insurance, defence, and commercial geospatial analytics
- Practical case studies demonstrating real-world challenges and solutions in disaster preparation, monitoring, damage assessment, and recovery operations
- Outcome-based evaluation of common approaches to emergency risk management, identifying strengths and limitations of current practice
- Coverage of future developments in data availability, analytical techniques, and climate risk assessment relevant to evolving environmental uncertainty
- Guidance on risk communication and decision-making frameworks that translate geospatial analysis into actionable operational and financial strategies
Designed for professionals in disaster management, emergency response, and the insurance industry, as well as researchers and advanced students in the geosciences, this book provides a structured, practice-oriented resource for applying geographic perspectives to quantify, communicate, and reduce disaster risk across sectors.
Table of Contents
Editors xv
List of Contributors xvii
Contributors and Acknowledgements xxix
Foreword xxxi
Preface: Geography Underpins Disaster Risk Management xxxiii
1 Defining Characteristics of Assets for Risk Assessment –Exposure and Vulnerability 1
Anirudh Rao, Catalina Yepes- Estrada, and Vitor Silva
1.1 Introduction 1
1.2 Overview of the Chapter’s Objectives and Scope 2
1.3 Exposure and Vulnerability: A DRM and DRR Perspective 3
1.4 Characteristics of Assets and Their Exposure and Vulnerability to Hazards 6
1.4.1 Different Types of Assets in the Context of Exposure 6
1.4.2 How Do Key Characteristics of These Assets Determine Their Vulnerability to Hazards? 7
1.4.3 Need for a Taxonomy System for Categorising Assets and Linking Exposure to Vulnerability 9
1.4.4 Geospatial and Temporal Context of Exposure and Vulnerability 9
1.4.4.1 Importance of the Geographic Context 9
1.4.4.2 The Time- Varying and Dynamic Nature of Exposure 11
1.4.4.3 The Role of the Historical and Geographical Contexts in Assessing Vulnerability 13
1.4.4.4 Impact of Different Codes/Regulations over Time 13
1.5 Case Study – How the Global Earthquake Model (GEM) Foundation Captures and Curates Exposure, Vulnerability and Value at Risk 14
1.5.1 Exposure Models Derived from Detailed Building Inventories 15
1.5.2 Exposure Models Derived from Building or Housing Censuses and Other Statistical Data 17
1.6 Case Study – The Spatial Finance Initiative GeoAsset Project 19
1.7 Conclusion 21
References 22
2 Common Approaches to Exposure and Vulnerability Data Across Risk Management Sectors 25
Charles Huyck, Marina Mendoza, and Melisa Huyck
2.1 Introduction 25
2.2 Types of Exposure Data 27
2.3 A Taxonomy for Exposure Data Classification 29
2.3.1 Level 1 – Global Data 32
2.3.2 Level 2 – Country- Level Exposure Data 33
2.3.3 Level 3 – Data Improvement at the Sub- national Scale 33
2.3.4 Level 4 – Aggregated Building- Specific Data 33
2.3.5 Level 5 – Site- Specific Data 35
2.4 Key Attributes and Considerations for Developing a Building Exposure Dataset 35
2.5 Use of EO Data for Exposure Development 38
2.6 Limitations and Challenges 40
2.7 Promising Trends in Exposure Development 42
2.7.1 Case Study – Enhancing Disaster Resilience Through Global Economic Disruption Index (GEDI) Implementation 43
Acknowledgments 45
References 45
3 Innovations in Spatial Exposure Modelling for Public Sector Disaster Risk Practitioners 49
Rashmin Gunasekera, Harriette Stone, Antonios Pomonis, James Daniell, Gonzalo Pita, and Bramka Jafino
3.1 Introduction 49
3.2 Case Studies of Exposure Modelling for the Public Sector 51
3.2.1 Case Study 1 – A Global Education Sector Exposure Model: Developing an Innovative Model That Is Fit for Purpose 51
3.2.1.1 Developing a Database of Education Infrastructure 51
3.2.1.2 Developing the Exposure Model 52
3.2.1.3 Application of the Model 52
3.2.1.4 Opportunities 52
3.2.1.5 Challenges 55
3.2.2 Case Study 2 – Improving Exposure Models Through Repeat Analysis of Past Disasters 56
3.2.2.1 Developing the Model 57
3.2.2.2 The Analysis and Results 60
3.2.2.3 Opportunities 62
3.2.2.4 Challenges 62
3.2.3 Case Study 3 – Incorporating Social Development and Gender Equity in Exposure Models 63
3.2.3.1 Developing the Timor- Leste Residential Exposure Model 63
3.2.3.2 Incorporating Socio- economic Status in the Exposure Model 64
3.2.3.3 Estimating Well- Being Losses Using the Residential Exposure Model 65
3.2.3.4 Opportunities 69
3.2.3.5 Challenges 70
3.2.4 Case Study 4 – Exposure for Public Sector Asset Management 71
3.2.4.1 Exploring the Requirements for an AIMS and the Challenges to Overcome in the Caribbean 71
3.2.4.2 Developing the Asset Information Management System in St Lucia 72
3.2.4.3 Opportunities 73
3.2.4.4 Challenges 74
3.2.5 Case Study 5 – Using Technology to Reduce Uncertainty in Building Data for City- Level Exposure Models 74
3.2.5.1 Collecting and Testing Accuracy of Building Data for Exposure 74
3.2.5.2 Opportunities 77
3.2.5.3 Challenges 77
3.3 Conclusion 77
References 78
4 Geographic Nature of Hazard and Risk 81
Michal Lörinc
4.1 Disaster Definition and Typology 81
4.1.1 What Makes a Disaster? 81
4.1.2 Temporal Resolution of Disasters 82
4.1.3 General Categorisation 82
4.1.4 Catastrophes in Re/Insurance 83
4.2 Geographic Aspects of Natural Disaster Risk 84
4.2.1 Geographic Distribution of Natural Hazards 84
4.2.1.1 Earthquakes 84
4.2.1.2 Volcanic Eruptions 84
4.2.1.3 Tropical Cyclones 85
4.2.1.4 Extratropical Cyclones 85
4.2.1.5 Floods 85
4.2.1.6 Severe Convective Storms 86
4.2.1.7 Droughts 86
4.2.1.8 Wildfires 87
4.2.2 Importance of Local Environmental Conditions 87
4.2.2.1 Topography and Orography 87
4.2.2.2 Soil and Ground Conditions 87
4.2.2.3 Hydrological Conditions and Drainage Systems 88
4.2.2.4 Vegetation and Ecosystem Health 88
4.2.3 Physical Vulnerability as a Factor of Risk 89
4.2.4 Economic Vulnerability and Insurance 90
4.2.5 Social and Environmental Vulnerability 90
4.3 How the Geographic Nature of Risk Changes 91
4.3.1 Climate Change 91
4.3.1.1 Temperature Extremes 91
4.3.1.2 Drought 91
4.3.1.3 Severe Convective Storms 92
4.3.1.4 Tropical Cyclones 92
4.3.1.5 Flooding 93
4.3.2 Climate Variability and ENSO 93
4.3.3 Socio- economic and Demographic Change 94
4.3.4 Changing Role of Insurance 94
4.4 Adapting to Current and Future Risk 96
4.4.1 Coastal Defences and Flooding 96
4.4.2 Inland Flooding 98
4.4.3 Severe Convective Storms 99
4.4.4 Temperature Extremes and Droughts 99
4.4.5 Earthquakes 99
4.4.6 Wildfires 100
4.5 Conclusion 100
References 100
5 Disaster Risk Reduction, Risk Mitigation 105
Stuart Fraser and Thaisa Comelli
5.1 Why Take a Geographic Perspective to DRR 105
5.2 History, Good Practices and Knowledge Frontiers 106
5.3 DRR and Adaptation Across Sectors 108
5.4 Unpacking Geographic Perspectives 109
5.5 Application of Geographic Perspectives Approaches in DRR and Adaptation 110
5.5.1 Methodological Approaches 111
5.5.2 Tools and Data to Build Geographic Perspectives 115
5.5.2.1 Data Portals and Decision Support Systems 115
5.5.2.2 Deeper Spatial Analysis and Risk Models 116
5.5.2.3 Spatial Planning and Policymaking 118
5.6 The Future of Geographic Perspectives for DRR and Adaptation: Three Key Points 119
5.6.1 Relying on Interdisciplinary Geographic Approaches for Improved Decision- Making at the Local Level 120
5.6.2 Closing Gaps in Geographic Risk Understanding and Analytics Globally 120
5.6.3 Grasping Different Future Options Through Inclusive and Equity- Focused Anticipatory Approaches 120
5.7 Conclusion 121
References 122
6 Insurance and Risk Transfer Mechanisms 127
Chris Ewing and Alec Wild
6.1 Introduction – Geospatial Data in Risk Transfer and Insurance 127
6.1.1 Assessing Risk Using Maps 127
6.1.2 Location Accuracy and Precision 132
6.1.3 Risk Transfer Value Chain and Geospatial Data Quality 133
6.1.4 Exposure Enrichment and Augmentation 134
6.2 Premium Pricing Considerations 134
6.2.1 Motor 136
6.2.2 Marine 136
6.2.3 Cyber 137
6.2.4 Health 141
6.2.5 Aviation 141
6.3 When Losses Occur 142
6.3.1 Claims/Loss Data and Analysis 142
6.3.2 Case Study – Real- Time Loss Forecasting for (re)Insurers 147
6.3.3 Business Interruption 147
6.3.4 Demand Surge 148
6.4 Catastrophe Model Components and Geospatial Data 148
6.4.1 Exposure – What Is at Risk 148
6.4.2 Hazard – Where, What, and How Frequent Is the Impact 151
6.4.2.1 Event Footprint Data for Earthquakes 151
6.4.2.2 Event Frequency/Severity Data for Atmospheric Perils 151
6.4.3 Vulnerability – Damageability of a Structure, Preparedness of a Population 152
6.5 Accumulation Management 153
6.5.1 Accumulation in Insurance 153
6.5.2 Accumulation in Reinsurance 154
6.6 Parametric Insurance and Insurance- Linked Securities 156
6.7 Catastrophe Pools 156
6.8 Conclusion 156
References 157
7 Disaster Preparedness in Fragile, Conflict- and Violence-Affected Humanitarian Settings 161
Madeline Ewbank, Laura E.R. Peters, Juliane Schillinger, Liesa Sauerhammer, Cornelia Scholz, Catalina Jaime, Tesse de Boer, and Simphiwe Laura Stewart
7.1 Introduction 161
7.2 The Complexities of Fragility, Conflict and Violence in Disaster Preparedness 163
7.2.1 Fragility 163
7.2.2 Conflict 164
7.2.3 Violence 165
7.2.4 Humanitarian Programming and Disaster Preparedness 166
7.3 Geospatial Tools to Detect FCV Spatial Patterns 167
7.3.1 Ethical Considerations 167
7.3.2 Perspectives and Tools 168
7.4 Multi- hazard/Multi- risk Analysis in FCV Settings 171
7.5 Geospatial Tools in Risk Analysis for FCV Settings 173
7.6 Conclusion 176
References 178
8 Event Response: Mobilisation and Logistics 185
Claire Byrne, Samir Gandhi, Mark Gillick, Edith Lendak, Naomi Morris, Claudia Offner, Matt Pennells, and Matthew Sims
8.1 Introduction 185
8.2 Mobilisation and Logistics 186
8.2.1 Case Study – Madagascar Cyclone Response February 2022 187
8.2.1.1 Background 187
8.2.1.2 Response Actions 187
8.2.1.3 Technologies Used 187
8.2.1.4 Outcomes and Lessons Learned 189
8.3 Logistical Frameworks 189
8.3.1 Local and National Frameworks 191
8.3.2 Regional Frameworks 191
8.3.3 International Frameworks 191
8.3.4 Case Study – Haiti Earthquake Response August 2021 192
8.3.4.1 Background 192
8.3.4.2 Response Actions 195
8.3.4.3 Technologies Used 195
8.3.4.4 Outcomes and Lessons Learned 195
8.4 Historical Context and Technological Advances 199
8.4.1 Technological Integration 200
8.5 Timeline of Events 201
8.5.1 Case Study – Belize Wildfires May and June 2024 203
8.5.1.1 Background 203
8.5.1.2 Response Actions 203
8.5.1.3 Technologies Used 204
8.5.1.4 Outcomes and Lessons Learned 207
8.6 Key Stakeholders 207
8.6.1 Case Study – Ukraine Complex Emergency 210
8.6.1.1 Background 210
8.6.1.2 Response Actions 210
8.6.1.3 Technologies Used 212
8.6.1.4 Outcomes and Lessons Learned 212
8.7 Communication and Knowledge Sharing Networks 213
8.8 Challenges and Solutions 213
8.9 Future Trends and Recommendations 216
8.9.1 Emerging Technologies 216
8.9.2 Policy and Framework Recommendations 218
8.9.3 Capacity Building 219
8.10 Conclusion 220
References 221
9 Real-Time Monitoring and Communication 225
Richard Teeuw
9.1 Introduction 225
9.2 The Disaster Risk Management Context 225
9.2.1 Comprehensive Preparedness vs. Rapid Targeted Responses 225
9.3 Real- Time Earth Observation (EO) Monitoring 227
9.3.1 Eyes in the Skies 228
9.3.2 Case Study – Using Real- Time Satellite Imagery in Response to a Pacific Cyclone Disaster 228
9.3.3 Early Warning Systems (EWS) 232
9.3.3.1 Hydrometeorological EWS 233
9.3.3.2 Geospatial Data Integration Systems 234
9.3.3.3 The United Nations (OCHA) Global Disaster Alerts and Coordination System (GDACS) 234
9.3.4 Case Study – The Previsico Flood Intel Platform 235
9.4 Real- Time Communications 238
9.4.1 Satellite Communication (Satcom) Systems 239
9.4.2 Local WiFi Hubs: Balloons and Drones 240
9.4.3 Case Study: World Food Programme Emergency Telecom Systems 241
9.4.4 Professional and/or Amateur Radio 243
9.5 Reducing Disaster Risk by Closing the Digital Data Divide 244
9.6 Conclusion 244
References 245
10 Damage Assessment 251
David Heathcote
10.1 Introduction 251
10.2 Data Acquisition 251
10.3 Windstorm Damage Assessment (Hurricanes and Storms) 253
10.4 Flood Damage Assessment 256
10.5 Wildfire Damage Assessment 258
10.6 Conflict and War Damage Assessment 260
10.7 Case Study: MIS Assessment Process for Hurricane Helene 262
10.7.1 Exposure Layer 262
10.7.2 Claims Layer 262
10.7.3 Building- Level Layer 264
10.7.4 Data Anomalies 264
10.7.5 Future of Assessments 266
10.8 Conclusion 268
References 269
11 Long-Term Resilience: Recovery Finance and Implementations of Lessons Learned 271
Alastair Norris and Claire Souch
11.1 Introduction: Defining Disaster Response vs. Long- Term Resilience 271
11.1.1 Case Study: Reduction in Tropical Cyclone- Related Deaths in Bangladesh from 1970 to 2024 273
11.2 Response and Recovery Finance: Foundations for Effective Recovery 275
11.3 Transitioning from Response to Recovery: Timeline and Key Needs 278
11.4 Short- to Medium- Term Recovery (Weeks to Months) 281
11.4.1 Case Study: Recovery and Reconstruction Following the Great East Japan Earthquake of March 2011 282
11.5 Long- Term Recovery and ‘Building Back Better’ (Months to Years) 284
11.6 Building Long- Term Resilience 286
11.7 Conclusion 290
References 291
12 Data Accuracy and Requirements: ‘What Data Are Appropriate?’ 297
Alec Wild, Heather Craig, James Knight, Charles Lan, Ryan Paulik, Liam Wotherspoon, and Conrad Zorn
12.1 Introduction 297
12.2 Navigating the Geospatial Terrain: Challenges and Considerations 297
12.3 The Unique Challenge Spectrum of Disaster Risk Management 298
12.4 Key Dimensions of Data Requirements 298
12.5 Case Study – Hunga Tonga– Hunga Ha’apai Eruption Response 299
12.6 Case Study – Assessing Indirect Impacts of Extreme Sea Level Flooding on Critical Infrastructure in South Dunedin 304
12.6.1 Hazard Data 305
12.6.2 Asset and Network Data 305
12.6.3 Results 309
12.7 Case Study – Development of Fragility Functions for the Agriculture Sector from Volcanic Tephra Fall 311
12.8 Case Study – Population Exposure and Evacuation Clearance Times in the Auckland Volcanic Field, New Zealand 316
12.9 Discussion 320
12.10 Conclusion 323
References 323
13 Communicating Uncertainty 329
Giacomo Favaron
13.1 Introduction 329
13.2 The Use of Decision Frameworks to Understand Uncertainty 330
13.3 Communicating Uncertainty While Navigating the DIKW Framework: Challenges and Implications for Disaster Risk Management 331
13.3.1 Why Effectively Communicating Uncertainty Matters in Disaster Risk Management 332
13.4 The Importance of Cartographic Design in Representing Uncertainty Effectively 332
13.4.1 Cartographic Techniques for Representing Uncertainty 332
13.4.2 Proposed Cartographic Techniques to Represent Uncertainty 333
13.4.3 Understanding Data Characteristics and Choosing Colour Palettes 337
13.4.4 Data Categorisation 337
13.4.5 Representation of Temporal Uncertainty 340
13.4.6 Considering Accessibility 340
13.5 Case Study – Analysing Uncertainty in Tropical Cyclone Forecasts 341
13.5.1 Putting Tropical Cyclones in Context 341
13.5.2 Sources of Uncertainty in Tropical Cyclone Forecasts and Forecasting with Ensembles 342
13.5.3 The Cone of Uncertainty: What It Is and How It Can Be Misinterpreted 343
13.5.4 Common Misconceptions About the Cone of Uncertainty 344
13.5.5 Beyond the Cone: Exploring Alternative Visualisations for Tropical Cyclone Uncertainty 344
13.5.6 From Tropical Cyclone Foresting to Impact Base Forecasting: Developing Tools to Support Pre- event Mitigation Actions Using Uncertainty Information 345
13.6 Case Study – The 2009 L’Aquila Earthquake and The Consequences of Miscommunication 348
13.6.1 Introduction 348
13.6.2 Is It Possible to Predict an Earthquake? 350
13.6.3 Understanding Risk Maps 350
13.6.4 Challenges of Historical Mapping Materials 351
13.6.5 The Importance of Probabilistic Seismic Hazard Analysis and Hazard Maps in Risk Assessment, Risk Management and Risk Mitigation 351
13.6.6 The Challenges of Communicating Risk Uncertainty for High Impact Low Probability Risks 354
13.6.7 Learning from the Past 355
13.7 Conclusion 357
References 357
14 Reporting and Decision-Making 363
Kelvin Wong
14.1 Introduction 363
14.2 The Importance of Audience 364
14.2.1 Types of Decision- Makers and Their Decisions 365
14.2.1.1 Designing Effective and Efficient Reporting for Decision- Making 365
14.2.1.2 Clarity and Succinctness 365
14.2.1.3 Scale and Frequency 366
14.2.1.4 Timeliness 367
14.2.2 Choosing the Right Format 367
14.2.3 Accuracy and Building Trust 368
14.2.4 Collaboration and Coordination 368
14.2.5 Understanding Socio- cultural Nuances 369
14.2.6 Ethical Considerations 369
14.2.7 Role of Technology and GIS 370
14.2.8 Barriers to Successful Communication 370
14.2.8.1 Physical Barriers 371
14.2.8.2 Psychological Barriers 371
14.2.8.3 Semantic Barriers 371
14.2.8.4 Cultural Barriers 372
14.2.8.5 Technological Barriers 372
14.3 Case Studies in Reporting and Decision- Making 373
14.3.1 Case Study 1 – Humanitarian 373
14.3.2 Case Study 2 – Oil and Gas 376
14.3.3 Case Study 3 – Risk Communication Consulting 378
14.4 Discussion 380
14.4.1 Types of Audience and Decision- Makers 381
14.4.2 Location and Geography 381
14.4.3 Format and Delivery Mechanisms 381
14.4.4 Priorities for Communication 382
14.4.5 Directionality of Communication 382
14.5 Conclusion 382
References 383
15 Wrapping Up and Looking Ahead 385
Chris Ewing, Matthew Foote, William Forde, and Tina Thomson
15.1 Representing the Elements at Risk – Exposure and Vulnerability 385
15.2 Disaster Preparedness and Risk Reduction 386
15.3 Event Mobilisation, Monitoring, Damage Assessment and Resilience Building 387
15.4 Communicating and Understanding Risk 388
15.5 A Call to Action to Advance Best Practice 390
15.5.1 Enhance Data Collection and Sharing 390
15.5.2 Foster Interdisciplinary Collaboration 390
15.5.3 Implement Real- Time Monitoring and Forecasting 391
15.5.4 Promote Community Engagement and Education 391
15.5.5 Develop Adaptive Policies and Frameworks 392
15.5.6 Invest in Resilience and Sustainability 393
15.5.7 Advocate for Global Cooperation and Knowledge Exchange 394
References 395
Glossary 397
Index 409
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