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Forest Fire Detection Economics

Forest Fire Detection Economics Robert S. McAlpine Ontario Ministry of Natural Resources Fire Detection Workshop Hinton, Alberta March 25, 2003 David L. Martell Faculty of Forestry University of Toronto Overview Basic Concepts Detection Methods Detection Patrol Routing Problem

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Forest Fire Detection Economics

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  1. Forest Fire Detection Economics Robert S. McAlpine Ontario Ministry of Natural Resources Fire Detection Workshop Hinton, Alberta March 25, 2003 David L. Martell Faculty of Forestry University of Toronto

  2. Overview • Basic Concepts • Detection Methods • Detection Patrol Routing Problem • Detection/Initial Attack System Model • Conclusion

  3. Life Cycle of a Forest Fire

  4. Value of Detection System • Need to assess detection system from an overall system perspective • Detection system objective is to find fires such that they can be controlled at reasonable cost and impact • Value of the detection system is the net reduction in total cost plus loss

  5. Detection Considerations • Value of the resource protected • Visibility • Probability of a fire occurring • Expectations of fire behavior • Potential for fire spread • Coverage by unorganized detection

  6. Detection probability is the probability you find the fire when you look in a cell Detection Probability • Partition the protected area into many small cells

  7. Aircraft Detection Methods Lookout Towers

  8. Lookout Towers Strategic Decisions 1. How many towers? 2. What locations?

  9. Fire Lookout Tower Location Models • Partition protected area into a large number of small rectangular cells • Identify potentially good tower sites

  10. Tower Location Models 1. Minimize the number (or cost) of towers required to cover all cells - may require double coverage for triangulation 2. Maximize the number of cells seen by a specified number of towers - use potential damage estimates to weight cells

  11. Aircraft Strategic Decisions 1. How many aircraft? 2. What hours? 3. What type?

  12. Aircraft TacticalDecisions 1. When to dispatch 2. Where to fly

  13. Detection Patrol Routing Problem • Partition the protected area into a large number of small rectangular cells • Predict the expected number of fires or probability of fires in each cell • Use vegetation, fire weather and “values at risk” map to identify potentially critical cells that “must” be visited • Develop the “best” patrol route(s) to visit all the cells that must be visited

  14. Simple Detection Patrol Routing Problem 1. Should you dispatch a detection patrol? 2. If you dispatch detection patrol, at what time?

  15. Simplifying Assumptions 1) Fire Started at 08:00 hours 2) Forward Rate of Spread of the Fire = 36 m/h 3) Fire Damage = $200 per hectare burned up until the time of detection

  16. Fire Loss Assuming Fire is Circular

  17. DetectionProbability Function

  18. Detection Patrol Routing Problem Suppose you look at 10:00 Expected Cost = (1,000 + 320 )×0.2 (find at 10:00) + Loss + (1,000 + 11,720)×(1-0.2) (public at 20:00) = 10,440

  19. Detection Patrol Routing Problem

  20. Towers vs Aircraft Aircraft • flexible • inexpensive • intermittent surveillance Towers • fixed • expensive • constant surveillance Use in low value forest with small detection budget Use in high value forest if have a large detection budget

  21. Measures of Detection System Effectiveness Cost per unit area protected (minimize with NO effort) Cost per fire detected (let the public find them all) Hours flown per fire detected (minimize with NO effort) Percent of fires detected by airborne observers (compete with the public) Average size at detection (ignores travel time, spread rate, etc.) Find fires so you can put them out at reasonable cost and damage (detection cost, suppression cost, fire damage)

  22. Detection/Initial Attack System Model Model that predicts the final sizes of historical fires given: • Actual fire report record • Actual fuel and fire weather information • Suppression by a perfect hypothetical initial attack crew Model provides an objective relative measure of how well the detection system worked on a single fire or collection of fires Does not indicate how well the system should perform

  23. Fire Behaviour • Fire Shape: wind driven ellipse model • Fire Growth: FBP to predict area, perimeter • Fire declared held when the fire line constructed equals 50% of the fire perimeter

  24. Fire Suppression Rate of Line Construction: RLC = B0 + B1× FI by fuel type

  25. Simple Containment Model Hypothetical Final Size: Predicted final size of a fire given the fire conditions and a hypothetical perfect initial attack crew that is dispatched as soon as the fire is reported Perfect Final Size: Final size of a fire given detection as soon as the fire starts, and a hypothetical perfect initial attack crew that is dispatched as soon as the fire starts Detection Loss = HF - PF (ha per fire)

  26. Average Annual Results (1980 - 85) • Year to year comparisons (e.g., before and after detection program changes) are valid • Direct comparison between regions questionable (values at risk and fire loads differ)

  27. How Well Should the Detection System Perform? Depends Upon: • Values at risk • Number of fires per year • Fire behaviour • Public detection system • Detection budget

  28. Thank YouDiscussion

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