Spatial ICTs for risk identification and risk reduction: Three geographic scales and three challenges Uwe Deichmann Development Research Group World Bank, Washington DC 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 Hazard probability Exposure Vulnerability Damages Losses Mitigation or risk transfer people, assetssocial/econ/phys conditions geophysical drivers policy analysis, costs/benefits e.g., average annual losses, loss exceedance curves damage ratios

Combining information on hazards … Severe Storms, 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