Geoinformation for Disaster and Risk Management - ISPRS

different times of day). Since no two cities are alike,
the transferability of such relationships needs to be
carefully examined. The broadest unit of analysis
considered in this conceptual framework is the
administrative city boundary (Tier 1). At Tier 1, the
approach considers three population estimation
models for which processing time, data requirement
and cost increase with information detail.
Model 1: City population, uses an areal overlay
methodology based on the simplified assumption
that population is uniformly distributed across the
city. This is a very simple case.
Model 2: Urban population, employs Quickbird
satellite images to extract the urban areas (oppose to
non-inhabited regions) in which the population is
supposed to be uniformly distributed. This
assumption is still an oversimplification.
Model 3: Occupancy-based population differentiates
occupancy categories within the urban areas so that
population can be estimated for each of the
categories (Figure 2).
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Damage information for disaster response
There is no substitute for real-time or near-real-time
data and information in the aftermath of a disaster.
Post-event activities require quick and accurate
information about damage and casualties to
coordinate a response to the catastrophe. Within the
re/insurance arena, geographically referenced
damage information is vital as an independent
source of loss estimation and to determine insurance
claims. For humanitarian relief, estimates of affected
population and casualties are critical for planning
relief and response activities. Although increasingly,
disaster information is becoming publicly available
through internet posting, its value is often limited by
the absence of metadata regarding its time and geolocation
(e.g., geotagging), both of which are central
to rendering it actionable.
Internet-based loss estimation
One example of a fully-georeferenced risk model is
the Internet-based earthquake loss estimation tool
InLET (Figure 3), designed and developed by
ImageCat (www.imagecatinc.com). InLET is the first
online real-time loss estimation system available to
emergency managers and responders. Immediately
following an earthquake, the United States
Geological Survey (USGS) broadcasts Internet alerts
using their ShakeCast platform. InLET which 'listens'
for such alerts, is automatically triggered and
produces loss estimation results based on details of
the earthquake event. Integrating hazard intelligence
with population and building inventory data from US
Census Bureau enables loss estimation algorithms to
immediately estimate fatalities and building damage
at the level of the census tract. The InLET framework
is readily transferable to other earthquake prone
parts of the World such as India.
Figure 2: Occupancy-based population estimates at Tier 1 using Model 3. The left figure displays the relative day time population
distribution, the right figure displays the population change between day- and night-time population.