Geoinformation for Disaster and Risk Management - ISPRS

Inventory data for pre-event risk modelling
From a theoretical standpoint, when developing
inventory data to support risk modelling, it is
important to follow the principal of model
consistency, whereby the level of detail with which a
given parameter is measured, is consistent with the
accuracy and the reliability of the risk model as a
whole. In a methodological context, pre-event risk
and loss estimation models operate respectively on
different spatial levels such as postcode, district,
municipality boundary, region or even country.
Traditional techniques for data acquisition and the
maintenance of up-to-date inventory databases are
very time- and cost-intensive. Taking India as an
example, more than 2 million people were involved
in the 2001 census building survey.
Of existing inventory development techniques, many
were conceived for small scale analyses, and as such,
do not match the requirements of either today's or
the future's megacities (see, for example, Prasad et
al., 2009). In the case of India, large city extents, rapid
and dynamic urban development, and very complex
urban structures, demand new methodologies for data
acquisition. Introducing efficiencies into the data
development sequence is a high priority.
Remote sensing and GIS/Web-GIS are increasingly
recognised as useful tools for facing the challenges of
inventory data development for megacities. Satellite
and aerial imagery have enormous potential to
provide detailed information at different resolutions,
across a range of time periods. In addition, with the
advent of internet-based records and data sharing, a
variety of statistical inventory data are now publicly
available. However, the accuracy of these datasets is
unknown and their quality is typically nonstandardised.
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Population inventory for Indian megacities
India is a prominent example of a nation where
urbanization is rapid, spatially varied, and
exceptionally dynamic. By 2050, India's total
population of 1.6 billion is expected to overtake that
of China (1.4 billion), of which 0.9 billion will be
urban dwellers (UN, 2008). If, as expected, high rates
of urbanisation are sustained in coming decades,
many cities will reach megacity status (more than 10
million inhabitants) in the near future. Further, due
to its geologic setting, India is regularly struck by
devastating earthquakes (Ravi, 2008). In 2001, the
state of Gujarat (northwest India) was hit by a 7.9M
event, causing widespread damage to buildings and
infrastructure and 20,000 fatalities (MCEER, 2009).
Only 4 years later, 88,000 people died in the Kashmir
region following a 7.6M earthquake (MCEER, 2009).
To meet the requirements for standardised and
efficient methods of inventory creation set by
professionals undertaking risk modelling, a new
approach is being developed through cooperation
between the Center for Disaster Management and
Risk Reduction Technology (CEDIM, www.cedim.de)
and ImageCat (www.imagecatinc.com), which uses a
combination of remote sensing and secondary
sources to generate inventory data products. As a
first step, a comprehensive catalogue of inventory
parameters employed in risk models spanning
different spatial levels was developed. This catalogue
includes 30 parameters subdivided into two
categories:
(1) Parameters that can be directly extracted from
satellite imagery such as building outlines
(2) Parameters that can be inferred by integrating
imagery with secondary data such as population
density.
The second step involved selecting of a high priority
‘pilot parameter’. From historical records of deadly
earthquakes, it is evident that the severity of human
loss is strongly related to occupancy levels of
vulnerable structures during an event. It may be
concluded that with the goal of minimising human
suffering and loss, information on population and its
distribution is a crucial parameter for comprehensive
disaster management. Accordingly, this was selected
as the ‘pilot parameter’
Test study site Ahmedabad (Gujarat, NW-India)
The rapidly growing urban agglomeration of
Ahmedabad in northern India was chosen as the test
site. At the time of the 2001 Census, approximately
3.5 million people lived in Ahmedabad. With an
annual population growth rate of 2.4%, the
population is projected to reach 4.3 million by 2011.
Ahmedabad can, without doubt, be called a megacity
of tomorrow, which is at risk from earthquakes
(Figure 1). In the case of the 2001 Gujurat event that
took place approximately 225km east of the Kutch
region, widespread ground motion with a recorded
peak ground acceleration of 0.11g (Eidinger et al.,
2001) caused significant building damage.