1. Journal of Homeland Security and
Emergency Management
Volume 5, Issue 1 2008 Article 2
Review of Measuring Vulnerability to Natural
Hazards: Towards Disaster Resilient Societies
Lucien G. Canton∗
∗
Lucien G. Canton, CEM (LLC), lcanton@pacbell.net
Copyright c 2008 The Berkeley Electronic Press. All rights reserved.

2. Review of Measuring Vulnerability to Natural
Hazards: Towards Disaster Resilient Societies
Lucien G. Canton
Abstract
Review of Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient Societies.
Reviewed by Lucien G. Canton, CEM, Emergency Management Consultant, Lucien G. Canton,
CEM (LLC), San Francisco CA.

3. Canton: Measuring Vulnerability to Natural Hazards 1
Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient
Societies. Jörn Birkmann, Editor. United Nations University Press, 2006.United
Nations University, Tokyo, Japan. 524 pages. ISBN 92-808-1135-5
Review by Lucien G. Canton, CEM, Emergency Management Consultant, Lucien
G. Canton, CEM (LLC), San Francisco CA.
The starting point for emergency management is an understanding of risk.
Risk assessment forms the basis for hazard reduction and capacity building. The
crucial element in understanding the risks facing a community is identifying the
vulnerability of the community to hazards. It is something of a shock then to
realize that, not only is there no single method for assessing vulnerability, but
there is not even agreement on basic terms, such as risk and vulnerability. This
problem is just one of the many issues that Measuring Vulnerability to Natural
Hazards: Towards Disaster Resilient Societies brings into sharp focus as it
considers the current state of vulnerability assessment.
Edited by Jörn Birkmann, Measuring Vulnerability to Natural Hazards:
Towards Disaster Resilient Societies uses the work of experts from across the
globe to discuss the issues surrounding the measurement of vulnerability at both
the micro and macro levels. The authors consider problems in defining
vulnerability, the use of indicators, existing methodologies and their
shortcomings, and directions for future research. International in scope and
academic in tone, Measuring Vulnerability to Natural Hazards: Towards Disaster
Resilient Societies is a welcome addition to any professional library.
Organization
The book is organized into five sections, each focusing on a specific area related
to measuring vulnerability. Part I examines the theories and principles related to
measuring vulnerability. In the initial chapter, Jörn Birkmann highlights the
problems involved in measuring vulnerability by discussing the lack of generally
accepted definitions of risk. More importantly, he argues persuasively for a
paradigm shift from hazard analysis to vulnerability assessment as a necessary
step to developing programs that actually reduce risk. The remaining chapters
build on this theme by considering the nature of vulnerability and the potential
indicators and corresponding proxy data that could be used to measure it.
Part II considers the impact of environment on vulnerability and discusses
the use of vulnerability assessment models in relation to long-term climate change
and other environmental events. Part III, however, is the true heart of the book.
An initial chapter by Mark Pelling provides an overview of global risk index
Published by The Berkeley Electronic Press, 2008

4. 2 JHSEM: Vol. 5 [2008], No. 1, Article 2
projects and is followed by detailed chapters on the Disaster Risk Index, Disaster
Risk Hotspots project, and the Americas Indexing Program. Two additional
chapters consider a multi-risk model based on existing European databases and a
field study in Tanzania to measure vulnerability. The section concludes with a
chapter by Erich Plate that offers an intriguing new concept for setting priorities
on the basis of a Human Security Index.
While Part III is concerned with aggregating information at the global or
national level, Part IV considers the measurement of vulnerability from a local
perspective, in essence moving from the quantitative to the qualitative. The five
chapters primarily report on various studies focused on small communities. Juan
Carlos Villagrán de León offers a new perspective by suggesting the measurement
of vulnerability by sector as a means shifting responsibility for risk reduction
from the central government to the appropriate sector.
Part V considers the measurement of the capacity of institutions to cope
with disaster. The authors consider both the thorny issue of defining coping
capacity and the difficulties in measuring it. They also consider methodologies for
increasing coping capacity through lessons learned from previous disasters.
An unlooked-for gem is the last chapter by Katharina Thywissen, in which
she attempts to create a core terminology by developing a comparative glossary.
Her work, like a similar project by Dr. Wayne Blanchard at FEMA, allows the
reader to consider multiple definitions for a term along with the original source or
sources of that definition.
Key Concepts
A number of recurring themes can be found in Measuring Vulnerability to
Natural Hazards: Towards Disaster Resilient Societies. One of the most critical is
the need to define terms. Even among a group that is as cohesive as the authors of
the various chapters in this book, there are still differences when they discuss the
definitions and inter-relationships of concepts, such as risk, vulnerability, hazard,
exposure, resilience, and coping capacity. A number of authors present models
that, while similar, do have some differences, supporting Birkmann’s point that
there is no single, generally accepted model for defining risk.
The reason for this disparity in definition is eloquently illustrated
throughout the book: vulnerability is a complex issue. One can measure
vulnerability as exposure to hazards or as potential loss to gross domestic product.
One can also consider the vulnerability of individuals, communities, or
institutions. Vulnerability can be divided by geographical region or by sector.
There are also inter-relationships and hazard nesting (a situation where one hazard
generates another, such as mudslides resulting from flooding). Consequently,
http://www.bepress.com/jhsem/vol5/iss1/2

5. Canton: Measuring Vulnerability to Natural Hazards 3
there can be no single definition of vulnerability without consideration of the
context in which the examination is taking place.
This issue of defining terms is important when one approaches
methodologies for measuring vulnerability. Vulnerability is measured through the
use of indicators that can be a single variable or an aggregate of data and may
include both quantitative and qualitative measures. Birkmann discusses the use
and importance of indicators and suggests criteria for the selection of indicators in
Chapter 2. In Chapter 3, Schneiderbauer and Ehrlich further refine this analysis as
it applies to social levels. Taken together, the chapters support the need to define
vulnerability as a prerequisite for selecting indicators.
In addition to issues related to definition, indicators also create their own
set of problems as noted by Mark Pelling in Chapter 7. In his summary of the
three models in the following chapters (Disaster Risk Index, Disaster Risk
Hotspots and the Americas Indexing Program), Pelling notes that one can
approach the measurement of vulnerability through deduction by examining past
losses (DRI and Hotspots); or one can use an inductive approach by measuring
potential losses (Americas Indexing Program). Both approaches have advantages
and disadvantages. The deductive approach is grounded in actual hazard
experience, but is heavily reliant on that experience. This reliance on past events
means that the deductive approach cannot be used to predict future risk
distributions. The inductive approach offers the advantage of being a predictive
model, but, depending on the selection of the variables, may be subject to political
manipulation.
Pelling’s study of the three models also considers related issues, such as
the overlap of data. He also points out problems with the use of economic data or
the use of impact on gross domestic product (GDP), particularly in the deductive
approach. Such measures may lack any information on long-range impacts or may
mask losses to the informal sector.
In considering data, there is also an issue of hazard-specific versus hazard-
independent focus. A hazard-specific focus relies on data from a specific type of
event. For example, Lebel and his colleagues consider the assessment of coping
capacity in relation to floods in Chapter 19. By contrast, Greiving in Chapter 11
considers multiple hazards in Europe in developing his model for vulnerability
assessment. Again, there are problems and advantages to both methods. One of
the strengths of the book is that the authors do not present any model as being
superior to the rest; they report their results and allow the reader to draw
conclusions.
Availability of data is a common problem encountered in all the models
considered throughout the book. For each indicator, researchers identify proxy
data based on their definition of vulnerability. However, data are frequently
unavailable or incomplete. This gives rise to concerns that indices only
Published by The Berkeley Electronic Press, 2008

6. 4 JHSEM: Vol. 5 [2008], No. 1, Article 2
approximate vulnerability and are not as precise or as objective as one may be led
to believe. This is supported by Pelling’s contention that a multi-hazard approach
is essential in measuring vulnerability and suggests that no single measure is
appropriate in all circumstances.
The ultimate use of any measurement of vulnerability is to assist in hazard
reduction. While the use of indices is effective on a national level, de-aggregating
data may not help much in determining effective hazard reduction at local levels.
For this, one must use a more qualitative approach. In practice, this usually means
the development of carefully crafted questionnaires that can be used either to
provide a self-assessment or as an interview tool by researchers. Bollin and Ria
Hidajat describe the use of a questionnaire in Indonesia to develop a community-
based risk index, translating qualitative responses into a quantitative model.
Wisner in Chapter 17 describes the use of a self-assessment questionnaire to
engage communities in hazard reduction.
In Chapter 16, Villagrán de León suggests an interesting public policy
approach by measuring vulnerability by sector. His contention is that, by
categorizing vulnerability by sector, one can transfer institutional responsibility
for hazard reduction from national disaster management agencies to the applicable
sector. He argues that ultimately the institutions in charge of the sector reduce
vulnerability and that categorizing vulnerability by sector can help these
institutions to recognize and accept responsibility for vulnerability reduction.
Vulnerability is also a function of the ability of institutions to cope with
the effects of hazards. However, coping capacity is one of the most difficult
variables to assess, as it is both difficult to quantify and subject to political
manipulation. Cardona proposes a Risk Management Index in the Americas
Indexing Program (Chapter 10), based on an institutional commitment to risk
identification, risk reduction, disaster management, and financial protection. In
Chapter 21, Billing and Madengruber adapt the Disaster Risk Index outlined by
Peduzzi in Chapter 8 to produce a composite disaster risk index to measure
coping capacities among countries. In the end, however, these quantitative
approaches, in the absence of any standards for disaster risk management, cannot
truly capture the largely qualitative essence of coping capacity.
One component of coping capacity is the financial ability of institutions to
deal with crisis. The search for a method of measuring economic vulnerability is
hampered by the lack of data demonstrating the true cost of disasters in terms of
both economic loss to the informal sector and of long-term costs and impacts.
Cardona approaches economic vulnerability through a Disaster Deficit Index,
based on the ratio of economic loss to economic resilience. Mechler and
associates in Chapter 20 consider the issue of financial vulnerability in developing
countries through the use International Institute for Applied Systems Analysis
Catastrophic Simulation (CATSIM) model. However, he warns that in both the
http://www.bepress.com/jhsem/vol5/iss1/2

7. Canton: Measuring Vulnerability to Natural Hazards 5
CATSIM model and Cardona’s indices, data may be missing or distorted and that
results should be viewed very carefully.
Future Directions
After reading Measuring Vulnerability to Natural Hazards: Towards Disaster
Resilient Societies one could view the current state of vulnerability assessment as
bleak. There are no agreed upon definitions and no standard assessment models.
The models that exist rely on data that is unavailable or incomplete. Yet this
would be a very distorted view. The disagreements on definitions are ones of
degree; researchers actually agree more than they disagree. It is appropriate that
some terms be defined in the context within which they operate. While there is a
need to use results carefully, the models that exist represent a quantum leap
forward for national disaster management agencies, particularly the work of
Cardona.
Birkmann does an admirable job of summing up future directions in
Chapter 23. Among his conclusions are:
• The use of quantitative versus qualitative measures depends on the level of
assessment. Quantitative methods may be more appropriate for identifying
national vulnerabilities, while a qualitative approach may be more useful
at the sub-national or community level.
• Hazard-specific and hazard-independent approaches to the measurement
of vulnerability each consider different aspects of vulnerability and use
different indicators. Future research should consider how to combine both
approaches to cover the full range of vulnerability.
• While global indexing has some utility, the use of indices may be too
vague to adequately describe how changing socio-economic and
environmental factors affect vulnerability. These projects need planning
and decision-making.
• Estimating economic vulnerability is a compromise between reliable
economic data based on past events and forecasted data based on
assumptions for the future. While there is a need to for grounding in
existing historical data, the shortcomings of that data need to be better
understood, and economic vulnerability estimation should include a
forecasting component.
• Vulnerability measurement is complex, despite attempts to simplify it
through the use of models. It is unlikely that there will ever be a single
accepted set of indicators or a single agreed-upon model. However,
significant progress could be made if it were possible to develop common
terminology for key components of vulnerability.
Published by The Berkeley Electronic Press, 2008

8. 6 JHSEM: Vol. 5 [2008], No. 1, Article 2
• Research into methods for vulnerability assessment would benefit from
more clearly defined goals and standards. These goals should help bridge
the gap between the theoretical and political decision-making.
Conclusion
Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient
Societies is an excellent summary of current research in the measurement of
vulnerability. In addition to the overall quality of the papers, Birkmann does an
excellent job of framing the discussion in his introductory and concluding
chapters. His analysis of current issues and future direction is particularly
noteworthy and serves to bring the book into focus.
The only minor quibble with the book is that it is an academic book,
written by academics for academics. As such, it can be rough going for the
layperson. This is unfortunate, as the politicians and emergency managers who
would most benefit from the information presented in the book will most likely
never read it. This is a loss, as this book has much to say about the nature of
disaster and potential policy implications and is well worth reading.
http://www.bepress.com/jhsem/vol5/iss1/2