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Spatial ICTs for risk identification and risk reduction:Three geographic scales and three challenges
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Spatial ICTs for risk identification and risk reduction: Three geographic scales and three challenges

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International Day for Disaster Reduction at the World Bank ...

International Day for Disaster Reduction at the World Bank

Disaster Risk Management in the Information Age

A joint training workshop by GICT, GFDRR, infoDev and LCSUW to mark the International Day for Disaster Reduction

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    Spatial ICTs for risk identification and risk reduction:Three geographic scales and three challenges Spatial ICTs for risk identification and risk reduction: Three geographic scales and three challenges Presentation Transcript

    • Spatial ICTs for risk identification and risk reduction: Three geographic scales and three challenges Uwe Deichmann Development Research Group World Bank, Washington DC <udeichmann@worldbank.org> International Day on Disaster Risk Reduction at the World Bank Disaster Risk Management in the Information Age October 8-9, 2008
    • ICTs are widely used, but challenges remain
      • Successful shift from disaster response to risk reduction
      • Bank support for risk analysis and risk management at all spatial scales
      • Spatial ICTs play a central role
      • GIS, GPS, remote sensing – linked by internet and other communication technologies
      • But: Technology is not the main problem. The bottlenecks are institutional!
    • Bank initiatives at three geographic scales
      • Global natural disaster risk
      • Country catastrophic risk assessment
      • Local risk identification
      • Awareness raising, priority setting, screening tool
      • Improving baseline information, methodologies, tools
      • Support specific interventions: mitigation & transfer
    • The standard risk assessment model applies across spatial scales Damages Losses Mitigation or risk transfer policy analysis, costs/benefits e.g., average annual losses, loss exceedance curves damage ratios Hazard probability Exposure Vulnerability people, assets social/econ/phys conditions geophysical drivers
    • Combining information on hazards … Severe Storms, 1981 - 2000 World Bank/Columbia University: Natural Disaster Hotspots Study 2005 based on storm track data compiled by UNEP-GRID Geneva Cyclone Frequency Global Analysis: Natural Disaster Risk Hotspots
    • … and exposure … Population distribution
    • … to generate risk profiles Multi-hazard mortality risk hotspots Updated global analysis forthcoming in the UN/WB Global Assessment Report on Disaster Risk Reduction 2009
    • Country catastrophic risk assessment
      • Operational risk assessments
        • E.g., Central America Probabilistic Risk Assessment
        • National level assessments in hotspot countries
      • Knowledge management: tools and guidance
        • MIRISK open source tool for risk assessment and guidelines on what to do about it
        • “ Guidance Note for Common Country Catastrophic Risk Assessment Methodology (C3RAM)”, GFDRR
        • Post disaster information sharing: “Using Data for Disaster Response” (PREM/GFDRR)
    • Local risk identification: Use of very high resolution satellite data
      • Image derived physical risk factors and exposure data
      • Complements GPS field data collection
      • Supports local risk identification
      • Case studies: Legaspi (Phl) and Sana'a (Yem)
    • Challenges
      • Capacity
        • Insufficient at local levels
        • Leading to highly centralized disaster management
      • Coordination
        • Inter-agency coordination within countries
        • Internationally (UN/national/NGOs) during disaster response
      • Content
        • Data and tools: limited access and black box models
        • Data readiness
    • What to do
      • Capacity
        • Learn from decentralization of other government functions
        • Invest in learning at the local level
      • Coordination
        • Use mix of incentives and enforcement while minimizing coordination costs (e.g., spatial data infrastructure)
        • High level agreements on binding protocols for IT use during disaster response
      • Content
        • Invest in data and analytical tools as public goods
        • Ensure data readiness well before disaster strikes