Effective use of spatial data and models to empower decision making


Published on

Richard Bernknopf's presentation to:

Roundtable - A National Framework for Natural Hazard Risk Reduction and Management: Developing a Research Agenda

Published in: Education
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • UsGS partnership with Natural Resources Canada. Two companies are involved: Emergeo (hazard vulnerability risk assessment) and CommunityViz Scenario 360 is the integration platform. United States Geological Survey (land use portfolio risk reduction decisions) What is new? Unique combination of tools Handles Multiple hazards (becoming a popular trend) Inclusion of natural hazard risk considerations into community/local planning sgog decisions for sustainable development. With an eye to scale up to higher levels of government. Needs a tool for Risk acceptability/policy process?
  • Squamish structures Exposure to hazard (200 year flood, Murray’s earthquake, Murray’s debris flow : earthquake most wide spread) Vulnerability (Flood and debris flow dominate earthquake) Risk (shift to floodplain)
  • Effective use of spatial data and models to empower decision making

    1. 1. Effective use of spatial data and models to empower decision making Identifying data, information, and modeling needs Richard Bernknopf Western Geographic Science Center A National Framework for Risk Reduction and Management November 15, 2006
    2. 2. Key questions <ul><li>Can natural science information be integrated with socioeconomic information? </li></ul><ul><li>Should quantitative forecasts about future physical and ecological outcomes be developed? </li></ul><ul><li>Can integrated models be developed that use quantitative forecasts to predict outcomes associated with different scenarios? </li></ul><ul><li>Can the implications of probabilistic outcomes be communicated effectively to decision makers? </li></ul><ul><li>How can uncertainty be controlled and reduced to inform decisions with natural science? </li></ul>
    3. 3. Policies and Decisions at Local Scale Insurance – Private / Public Exposure, Coverage, and Cost Mitigation – Private and Public Protection Strategies Land Use – Zoning and Land Transfers Emergency Preparedness - Warnings and Response Adaptation - Resilience Comparison of frequency and size of loss by decade for all natural hazards at national scale Source: Nishenko and Silves, 2006
    4. 4. Seismic Events and Probabilities (in 50 years) Repeat of 1811-1812 (magnitude 7.7): 10% Magnitude about 6.0 or greater: 25% Liquefaction Zone: Probability greater than 60% Issues: strengthening building codes for new commercial and industrial development to mitigate the consequences of seismic events; estimating the economic impact of scientific uncertainty on loss estimation Seismic risk mitigation in Memphis, TN: Quantitative policy analysis at local scale
    5. 5. Comparison of typical damage patterns <ul><li>Key difference between these patterns is the “lumpy” nature of spatially dependent patterns. This implies that destroyed parcels are much more likely to occur together than under independence. </li></ul>Spatially independent damage pattern Spatially dependent damage pattern Less severe Less severe Severe Severe More severe More severe
    6. 6. CommunityViz Natural hazard risks for sustainable development of Squamish, British Columbia, Canada                                                                            
    7. 7. Squamish, BC Multiple Hazards Building risk <ul><li>Earthquake exposure is most wide spread, but floods is the dominating source of the building risk </li></ul><ul><li>Debris Flow is an extremely rare but catastrophic event, debris fan is largely undeveloped but is under development pressure </li></ul><ul><li>Population will double in next 25 years </li></ul><ul><li>Spatial data used in risk assessment of future growth plans, GIS-based model (LUPM) for risk analysis of risk reduction strategies </li></ul><ul><li>Floods prioritized, planners updating flood management plan </li></ul><ul><li>Test: what spatial data, analysis, methods, models will the flood management plan embrace? </li></ul>
    8. 8. The future of moderate resolution spatial data <ul><li>Landsat </li></ul><ul><ul><li>High quality, moderate resolution spatial data </li></ul></ul><ul><ul><li>Valuable to public agencies, research scientists, and private firms </li></ul></ul><ul><ul><li>Future questions on resolution, frequency, and types of data </li></ul></ul><ul><li>Issues: </li></ul><ul><ul><li>Is there a market for moderate spatial resolution data? </li></ul></ul><ul><ul><li>Is a federal subsidy for collection and distribution appropriate? </li></ul></ul><ul><ul><li>What information is needed to make political and economic choices in selecting a data platform? </li></ul></ul>Manager No U.S. Govt. Commission Combination U.S. National Commercial Integrated Program Partnership 3 Satellites Z 10 Meters Multiple Agency Public/Private 2 Satellites Y 20 Meters Single Agency Government 1 Satellite X 30 Meters Governance Ownership Number of Satellites Spectral Sensors Image Resolution
    9. 9. Research Questions <ul><li>What mix of information and model development is needed to best inform decisions? </li></ul><ul><li>What characteristics of information are best suited to reduce and manage risk for natural hazards? </li></ul><ul><li>Resolution / scale </li></ul><ul><li>Uncertainty </li></ul><ul><li>Frequency of acquisition </li></ul><ul><li>What types of information can change choices? </li></ul><ul><li>Indicators </li></ul><ul><li>Thresholds </li></ul><ul><li>How is the information best communicated? </li></ul><ul><li>Representation </li></ul><ul><li>Integration </li></ul><ul><li>Delivery </li></ul>