Achievements in Wildland Fire Risk Mapping

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Achievements in Wildland Fire Risk Mapping
Acquis enCartographiedu Risque dIncendies de
Forêt
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Wildland Fire Risk Mapping

• Deliverables
• Wildland fire danger and hazards a state of the
  art
• Common methods for mapping the wildland fire
  danger
• Towards an Euro-Mediterranean Wildland Fire
  Danger Rating System

• Objectives
• Analyse the structure of existing wildland fire
  danger indexes
• Design an Euro-Mediterranean Fire Danger Rating
  System

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Wildland Fire Danger and Hazards a state of the
art (D-08-02, D-08-07)

• Wildland fire structure and terminology on fire
  risk
• Fire risk issues
• Temporal and spatial issues
• Fire management and risk assessment
• Risk variables
• Vegetation
• Climatic and meteorological
• Topography
• Anthropogenic variables

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Common methods for mappingthe wildland fire
danger (D-08-05)

• Methods for wildland fire risk mapping
• Dynamic fire risk indices
• Static-structural danger indices
• Operationally applied methods for fire danger
  estimation in Mediterranean countries
• Short-term
• Long-term
• Inventory of existing databases
• Cartographic interfaces for the dissemination of
  fire danger indices

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Scheme of the Euro-Mediterranean Wildland Fire
Risk Index (EM-WFRI) (D-08-03, D-08-06)
Satellite index
Fuel moisture
Ignition Danger Index
Meteo Index
Probability of ignition (human factors)
Human ignition
Fuel properties
Propagation Danger Index
Wind flows
EM - WFRI
Topography
Population exposition
Environmental value
Vulnerability Index
Economic value
Potential soil erosion
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Fuel Moisture (Satellite Information)
FMCg -57.103 284.808 x NDVI 0.089 x ST
136.75 x FDg FMCc 70.195 53.520 x NDVI
1.435 x ST 122.087 x FDc
(a)
(b)
Live fuel moisture content map (August, 10th
2004)
Observed and estimated FMC values for grasslands
(a) and C. ladanifer (b).
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Fuel moisture(Meteorological Index)

• Correlation between meteorological variables and
  environmental and topographic variables
• elevation ( r -0.72/-0.97),
• aspect (r -0.34/-0.53),
• slope (r -0.44/-0.70),
• sea distance (-0.40/-0.93)
• Multiple regression
• r 0.97 for minimum and maximum temperature of
  January and July
• Spatial interpolation of meteorological index
  value
• Interpolation of the meteorological parameters of
  the index (temperature, wind)
• Interpolation of the meteorological index

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Spatial interpolation of meteorological risk index
(c)
(a)
Interpolation of meteorological risk index
a) high resolution -50 x 50 m- b) low
resolution -1 x 1 km- Meteorological risk
index from interpolated variables c) high
resolution -50 x 50 m-
(b)
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Probability of Ignition(Human Factors)
Landuse types
Urban density
Road network
Structural forest fire ignition risk
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Probability of Ignition(Human Factors
occurrence)
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Scheme of the Euro-Mediterranean Wildland Fire
Risk Index (EM-WFRI)
Satellite index
Fuel moisture
Ignition Danger Index
Meteo Index
Probability of ignition (human factors)
Human ignition
Fuel properties
Propagation Danger Index
Wind flows
EM - WFRI
Topography
Population exposition
Environmental value
Vulnerability Index
Economic value
Potential soil erosion
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Propagation Danger Index
Rate of Spread (RS)
Propagation Danger Index (PDI)
Flame Length (FL)
EU SPREAD Project, 2004
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Vulnerability Index Environmental value

• Landscape Value
• Singularity
• Diversity
• Connectivity
• ......

CORINE LAND COVER
Environmental Value

• Ecological
• Value
• Natural protected areas
• Habitat of importance
• .....

NATURA 2000 NETWORK
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Vulnerability Index Potential soil erosion
Coefficients ascribed to the four soil erosion
factors used to estimate erosion risk
Erosion Index Slope Vegetation density Fire
severity Soil erodibility
Low 5 Intermediate 6 15 High 16-26 Very
high 27
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Vulnerability Index Potential soil erosion
Slope
Vegetation density
Fire severity
Soil erodibility
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Conclusions

• The components and structure of a risk index
  have been identified.
• Several examples have been shown to demonstrate
  their efficiency.
• The remaining challenge is to acquire better
  data necessary for risk estimation at the
  European scale.
• A GIS can be easily used for the generation and
  integration of the variables, and a map web
  server could be used for the distribution of the
  data and presentation of the risk.
• Two scales must be considered independently
• The European scale provides deciders with a
  global vision of the risk.
• The local scale provides an operational basis
  upon which local foresters and firemen can make
  practical decisions.