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Assessing Natural Hazard Risk in Urban Areas. Henrike Brecht Louisiana State University. Emergency Management Higher Education Conference, June 7, 2007 . Why a Risk Index?. Identifying Risk: Key element in disaster reduction Enables informed policy making Index:

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assessing natural hazard risk in urban areas

Assessing Natural Hazard Risk in Urban Areas

Henrike Brecht

Louisiana State University

Emergency Management Higher Education Conference, June 7, 2007

why a risk index
Why a Risk Index?
  • Identifying Risk:
    • Key element in disaster reduction
    • Enables informed policy making
  • Index:
    • Summarizes a body of knowledge
    • Easy to understand
    • Facilitates comparisons

Emergency Management Higher Education Conference, June 7, 2007

urban risk index
Urban Risk Index
  • Follow-up of World Bank Disaster Hotspots
  • Multi-hazard index
  • All cities worldwide with more than 100,000 inhabitants
  • Outcome: Relative risks of
    • mortality
    • economic losses

Emergency Management Higher Education Conference, June 7, 2007

what is risk
What is Risk?

Risk = Hazard x Exposed Elements x Vulnerability

  • Hazard
    • Derived from historic hazard data
  • Exposed Elements
    • City Population
    • City GDP
  • Vulnerability
    • Population vulnerability: derived from historic death tolls
    • Economic vulnerability: derived from historic economic losses

Emergency Management Higher Education Conference, June 7, 2007

data inputs hazards
Data Inputs: Hazards
  • Five major hazards
  • Vector data was gridded, raster data was resampled at 1 km resolution.

Emergency Management Higher Education Conference, June 7, 2007

data inputs cyclones
Data Inputs: Cyclones

Emergency Management Higher Education Conference, June 7, 2007

data inputs landslides
Data Inputs: Landslides

Emergency Management Higher Education Conference, June 7, 2007

data inputs floods
Data Inputs: Floods

Emergency Management Higher Education Conference, June 7, 2007

data inputs earthquakes
Data Inputs: Earthquakes

Emergency Management Higher Education Conference, June 7, 2007

data inputs exposed elements
Data Inputs: Exposed Elements
  • City population numbers (Henderson)
  • City GDP (World Bank)
  • City footprints: GRUMP (Global Rural-Urban Mapping Project) by CIESIN

Emergency Management Higher Education Conference, June 7, 2007

data inputs exposed elements1
Data Inputs: Exposed Elements

Emergency Management Higher Education Conference, June 7, 2007

data inputs vulnerability
Data Inputs: Vulnerability
  • Not based on social vulnerability indicators
  • Damage rates by hazard
  • EM-DAT (Emergency Disaster Database)
  • Population vulnerability:
    • historic death tolls per hazard
  • Economic vulnerability:
    • economic loss rate per hazard

Emergency Management Higher Education Conference, June 7, 2007

outcomes
Outcomes
  • For each city
    • Mortality risk index
    • Economic risk index
  • Relative risk levels

Emergency Management Higher Education Conference, June 7, 2007

earthquake mortality risk
Earthquake Mortality Risk

Emergency Management Higher Education Conference, June 7, 2007

conclusion
Conclusion
  • Index is a comprehensive summary and enables comparisons
  • Guides policy making and resource allocation
  • Index creation is impeded due to lack of accurate data
  • Macro analysis which does not replace careful risk assessments for cities

Emergency Management Higher Education Conference, June 7, 2007

a glance ahead
A Glance Ahead
  • Individual city assessment
  • Improve global flood and landslide hazard data
  • Improve global loss data

Emergency Management Higher Education Conference, June 7, 2007

slide17
Thank you.

Henrike Brecht

henrike@hurricane.lsu.edu

Emergency Management Higher Education Conference, June 7, 2007