 |
| Titel |
A Globally Consistent Methodology for an Exposure Model for Natural Catastrophe Risk Assessment |
| VerfasserIn |
Rashmin Gunasekera, Oscar Ishizawa, Bishwa Pandey, Keiko Saito |
| Konferenz |
EGU General Assembly 2013
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250076519
|
|
|
|
|
|
| Zusammenfassung |
| There is a high demand for the development of a globally consistent and robust exposure data
model employing a top down approach, to be used in national level catastrophic risk profiling
for the public sector liability. To this effect, there are currently several initiatives such as
UN-ISDR Global Assessment Report (GAR) and Global Exposure Database for
Global Earthquake Model (GED4GEM). However, the consistency and granularity
differs from region to region, a problem that is overcome in this proposed approach
using national datasets for example in Latin America and the Caribbean Region
(LCR).
The methodology proposed in this paper aim to produce a global open exposure dataset
based upon population, country specific building type distribution and other global/economic
indicators such as World Bank indices that are suitable for natural catastrophe risk modelling
purposes. The output would be a GIS raster grid at approximately 1 km spatial resolution
which would highlight urbaness (building typology distribution, occupancy and use)
for each cell at sub national level and compatible with other global initiatives and
datasets. It would make use of datasets on population, census, demographic, building
data and land use/land cover which are largely available in the public domain. The
resultant exposure dataset could be used in conjunction with hazard and vulnerability
components to create views of risk for multiple hazards that include earthquake,
flood and windstorms. The model we hope would also assist in steps towards future
initiatives for open, interchangeable and compatible databases for catastrophe risk
modelling.
The findings, interpretations, and conclusions expressed in this paper are entirely those of
the authors. They do not necessarily represent the views of the International Bank for
Reconstruction and Development/World Bank and its affiliated organizations, or those
of the Executive Directors of the World Bank or the governments they represent. |
|
|
|
|
|
|