forest fire detection in the wildland-urban interface james barnier wisconsin department of natural...
TRANSCRIPT
Forest Fire Detection in the
Wildland-Urban Interface
James Barnier
Wisconsin Department of Natural Resources
Division of Forestry
FERIC Wildfire Detection Workshop
March 25 – 27, 2003
Texas
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New HampshireMassachusetts
Connecticut
Alaska
Alaska
Delaware
Alaska
Alaska
QUEBEC
ONTARIO
ALBERTAMANITOBA
BRITISH COLUMBIA
NUNAVUT
SASKATCHEWAN
NORTHWEST TERRITORIES
NEWFOUNDLAND
NEW BRUNSWICK
YUKON TERRITORIES
Several Detection Options:
• Public reporting
• Fixed lookouts
• Ground patrols
• Air patrols
• Lightning detectors
• Satellite imagery
911 Availability
Choice of a Detection Method:
• Risk
• Hazard
• Value
Research Objective:
• Evaluate the performance and cost-effectiveness of public and organized wildfire detection methods in the wildland-urban interface
The Study Area:
Forest covertypes
Maple-Birch26%
Aspen-Birch29%
Spruce-Fir6%
Pine9%
Other30%
Socio-economic importance
• 90 thousand direct jobs
• $3.3 billion in wages
• $5.4 billion in value added
• 2+ million hectares of parks and conservation areas
• Over 8 million visitors annually
Settlement patterns
• 1.5 million residents
• 16 persons per square kilometre
• $45.8 billion in property values
Wisconsin’s detection system
• 95 fixed lookouts
• Public reporting
• Air patrols
• Ground patrols
Wildfire causes
Humans69%
Lightning2%
Railroads8%
Other21%
Suppression techniques
• Ground attack
• Type VII-X engines and/or Type IV engines with Type IV tractor plows
Analytical Methods:
• Cost-benefit analyses
• Tukey’s multiple comparison tests of performance measures
Costs & benefits of lookout detection
Costs Benefits
• Maintenance • Suppression Costs
• Labor • Property Damage
• Depreciation • Resource Values
• Deterrence Values
A benefit function
• Lookout benefits assessed relative to public detection
PLLPL VVCCB
Data:
• Two separate but linked datasets
• 4,690 individual fire reports (1987-1995)
• 711 addendum reports from (1992-1995)
A suppression cost model
• Model estimated for three covertype/ fuel model combinations
• Data included only those observations when lookouts were staffed
Results – Economic EffectivenessStatewide
• Protected 238 ha from wildfire damage
• Reduced suppression costs by $12 k
• Prevented $591 k in property damage
• Each $1 cost => $6 savings
A closer look
0
200
400
600
800
1000
1200
$ (0
00's
)
1992 1993 1994 1995
Year
Lookout Cost
Suppression Savings
Damage Prevention
• Protected 1.6 ha from wildfire
• Saved $86 in suppression costs
• Prevented $4,100 in property damage
Per fire
Administrative region
• Area saved and suppression costs saved were not statistically different
• Property damage prevented and number of wildfires detected differed significantly
A closer look
0
1
2
3
4
5C
-B R
atio
Area
Individual lookouts
• Lookout performance was highly variable
• Lookouts that detected more fires saved area and generated more benefits
A closer look
0
25
50
75
100
0 25 50 75 100
Percentage of Lookouts
Cu
mu
lati
ve P
erce
nt
Sightings
Area Saved
Total Savings
Results – Detection Performance:Wildfire sightings
Public62%
Air Patrol4%
Lookout34%
Detection lag
0
5
10
15
20
Min
ute
s
Public Lookout Air Patrol
AA
Final size
0.0
0.5
1.0
1.5
2.0
Hec
tare
s
Public Lookout Air Patrol
A
B
AB
Suppression cost
0
50
100
150
200
250
300
1995
$
Public Lookout Air Patrol
A
B
AB
Conclusions:
• Fixed lookouts were cost-effective
• Majority of benefits attributable to property damage prevention
• Performance highly variable
Conclusions (Continued):
• Small number of lookouts generated majority of benefits
• Public and lookouts see different wildfires
• Opportunities exist to enhance wildfire detection