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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

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
Overview
  • Basic Concepts
  • Detection Methods
  • Detection Patrol Routing Problem
  • Detection/Initial Attack System Model
  • Conclusion
value of detection system
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
detection considerations
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
detection probability

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
lookout towers
Lookout Towers

Strategic Decisions

1. How many towers?

2. What locations?

fire lookout tower location model s
Fire Lookout Tower Location Models
  • Partition protected

area into a large

number of small

rectangular cells

  • Identify potentially good tower sites
tower location models
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

aircraft
Aircraft

Strategic Decisions

1. How many aircraft?

2. What hours?

3. What type?

aircraft12
Aircraft

TacticalDecisions

1. When to dispatch

2. Where to fly

detection patrol routing problem
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
simple detection patrol routing problem
Simple Detection Patrol Routing Problem

1. Should you dispatch a

detection patrol?

2. If you dispatch

detection patrol, at

what time?

simplifying assumptions
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

detection patrol routing problem18
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

towers vs aircraft
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

slide21

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)

detection initial attack system model
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

fire behaviour
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
fire suppression
Fire Suppression

Rate of Line Construction:

RLC = B0 + B1× FI by fuel type

simple containment model
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)

average annual results 1980 85
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)
how well should the detection system perform
How Well Should the Detection System Perform?

Depends Upon:

  • Values at risk
  • Number of fires per year
  • Fire behaviour
  • Public detection system
  • Detection budget