GEOSCIENCE AUSTRALIA Quantifying Social Vulnerability: A methodology for identifying those at risk to natural hazards Dwyer, A., Zoppou, C., Nielsen, O., Day, S. & Roberts, S. Record 2004/14 SPATIAL INFORMATION FOR THE NATION Quantifying Social Vulnerability: A methodology for identifying those at risk to natural hazards Anita Dwyer, Christopher Zoppou, Ole Nielsen Risk Modelling Group, Geohazards Division, Geoscience Australia, Canberra, Australia Susan Day National Centre for Social and Economic Modelling (NATSEM), University of Canberra, Canberra, Australia Stephen Roberts Department of Mathematics, Mathematical Sciences Institute, The Australian National University, Canberra, Australia Department of Industry, Tourism and Resources Minister for Industry, Tourism and Resources: The Hon. Ian Macfarlane, MP Parliamentary Secretary: The Hon. Warren Entsch, MP Secretary: Mark Paterson Geoscience Australia Chief Executive Officer: Neil Williams c Commonwealth of Australia 2004 This work is copyright. Apart from any fair dealings for the purposes of study, re- search, criticism or review, as permitted under the Copyright Act, no part may be reproduced by any process without written permission. Inquiries should be directed to the Communications Unit, Geoscience Australia, GPO Box 378, Canberra City, ACT, 2601. ISSN: 1448-2177 ISBN: 1 920871 09 8 GeoCat No. 61168 Bibliographic reference: Dwyer, A., Zoppou, C., Nielsen, O., Day, S., Roberts, S., 2004. Quantifying Social Vulnerability: A methodology for identifying those at risk to natural hazards. Geoscience Australia Record 2004/14 Geoscience Australia has tried to make the information in this product as accurate as possible. However, it does not guarantee that the information is totally accurate or complete. THEREFORE, YOU SHOULD NOT RELY SOLELY ON THIS INFOR- MATION WHEN MAKING A COMMERCIAL DECISION. 2 Contents Contents iii Foreword v Acknowledgments vi Executive Summary vii Introduction 1 1 Indicator Selection 8 1.1SocialIndicators............................ 8 1.2 Social vulnerability and indicators . ................ 9 1.2.1 Study 1: Earthquake Disaster Risk Index ........... 9 1.2.2 Study 2: Cities Project ..................... 12 1.2.3 Other vulnerability indicator studies . ........... 13 1.3 Selection Criteria . ........................... 14 1.3.1 Criteria . ........................... 15 1.4 Selection of vulnerability indicators . ................ 16 2 Risk Perception Questionnaire 18 2.1 Indicators and measurement ...................... 18 2.2Perceptionofrisk............................ 19 2.3 Questionnaire development . ...................... 20 2.3.1 Collectionofnationaldata................... 20 2.3.2 Generation of hypothetical individuals . ........... 28 2.3.3 Questionnaire design ...................... 28 2.3.4 Respondent demographics . ................ 29 2.4 Questionnaire results .......................... 30 3 Decision Tree Analysis 32 3.1 Decision trees and social vulnerability . ................ 32 3.2 Perception based classification ..................... 33 3.3Decisiontreeanalysis.......................... 35 3.4 Analysis of the risk perception questionnaire . ........... 35 3.4.1 Assigning classes of vulnerability ............... 37 3.4.2 Developingdecisionrules................... 37 iii 3.4.3 Therelativeimportanceofthe15indicators.......... 42 3.5Decisionrulefindings.......................... 43 4 Synthetic Estimation 46 4.1 Perth Cities Project ........................... 47 4.1.1 StudyArea........................... 47 4.2Syntheticestimation........................... 48 4.3SyntheticestimatesforthePerthCasestudy.............. 50 4.3.1 Matching questionnaire variables ............... 50 4.4 Social vulnerability in the Case Study area ............... 52 4.4.1 Estimated social vulnerability of the study area . .... 53 4.5 Mapping social vulnerability using hazard scenarios . ..... 54 4.5.1 Mapped scenarios . ...................... 54 4.6Usingtheresults............................ 63 5 Discussion 66 5.1 Comparison with the Cities Project methodology ........... 67 5.2Limitationsandfuturework...................... 69 5.2.1 IndicatorSelection....................... 69 5.2.2 Risk Perception Questionnaire . ................ 69 5.2.3 DecisionTreeAnalysis..................... 70 5.2.4 Syntheticestimation...................... 70 5.3Areasforrefinementandfurtheranalysis................ 71 A Risk Perception Questionnaire 72 B Decision Tree Methodology 76 C Microsimulation 81 D Validation 84 Bibliography 86 Index 90 iv Foreword The occurrence of natural hazards is not a phenomenon of recent times, however, un- derstanding the risk from natural hazards is a relatively recent trend and is currently increasing at a greater rate than ever before. As population and infrastructure increases, social conditions fluctuate and the relationship between humans and their environment becomes more complex. All of these factors, and more, contribute to the wider picture of risk, including risk from natural hazards. While natural hazards will continue to occur, their capacity to become a disaster or merely a manageable event depends on many factors, including the magnitude of the hazard, the vulnerability of people and their communities, the built environment and political systems. This report focuses on certain aspects of social vulnerability and its role in con- tributing to the risk from natural hazards. In particular, the study introduces a unique method of measuring the vulnerability of individuals within a household in order to contribute to the development of comprehensive natural hazard risk assessments. The research undertaken for this report has been driven by two needs: firstly, to develop a custom-made methodology of quantifying social vulnerability that can be incorpo- rated into the risk models being developed by the Risk Research Group at Geoscience Australia. The Risk Research Group undertakes natural hazard research for the Aus- tralian Government, with the aim of developing risk models that assist decision-makers in better managing natural hazard risk to Australian communities. Secondly, the re- search outlined in this report has been influenced by a need to integrate social issues with hazard model development in order to investigate the greater risk to communities. Underlying this research is the need for a practical, albeit experimental, methodology of measuring elements of social vulnerability. Therefore, the report is a step-by-step account of the methodology development that aims to measure one aspect of social vulnerability, the vulnerability of an individual within a household, as a means of identifying those at risk to natural hazards. v Acknowledgments We would like to thank Matt Hayne, Project Leader of the Risk Assessment Method- ologies Project at Geoscience Australia for his support in the development of this study and his feedback on the report. Thanks also to Philip Buckle and John Handmer for their willingness to share their expertise, ideas and time with regards to social vulner- ability over the past two years. Thank you also to David Robinson for his review and constructive comments. Thank you to Dr Mihael Ankerst from The Boeing Company, Seattle, Washington for providing the the Perception Based Classification (PBC) software. And finally, thank you to all the people who completed the risk perception questionnaire. vi Executive Summary In this study, a methodology is developed to assess the vulnerability of individuals within households to risk from natural hazards. The methodology introduces a tech- nique for measuring certain attributes of individuals living within a household that contribute to their vulnerability to a natural hazard impact. The methodology has four main steps; Step 1: Indicator Selection As the study is focusing specifically on measuring vulnerability, the indicators se- lected have been restricted to quantifiable indicators. Thirteen vulnerability indicators and two hazard indicators indicators were selected for the study. The thirteen indi- cators are: Age, Income, Gender, Employment, Residence Type, Household Type, Tenure Type, Health Insurance, House Insurance, Car Ownership, Disability, English Language Skills and Debt/Savings. The two hazard indicators, residence damage and injuries, were included so that the following steps in the study were linked to a haz- ard context. The indicators are specific to people living in urbanised areas within an Australian city and were selected using selection criteria outlined in Chapter One. Step 2: Risk Perception Questionnaire In an attempt to identify how these indicators contribute to the vulnerability of a person within a household, a risk perception questionnaire was developed. The questionnaire was a means of collecting data on perceived vulnerability in lieu of the availability of actual vulnerability data. The questionnaire respondents were asked to rank the ability of hypothetical individuals to recover from a natural hazard impact based on their own perceptions of the situation. The hypothetical individuals were developed using the 15 indicators. The questionnaire was presented to ‘experts’ of disaster risk research and ‘non-experts’ for comparative purposes. The questionnaire results provided 1100 ranked hypothetical individuals, each with a unique set of indicator attributes. Step 3: Decision Tree Analysis Decision tree analysis is a classification methodology used to analyse and classify large sets of data. In this study, decision tree analysis was applied to the questionnaire