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FOMFIS Fo rest Fire M anagement and Fi re Prevention S ystem D. Kallidromitou Managing Director Epsilon International SA Monemvasias 27, 151 25 Marousi Athens-Greece e-mail: epsilon@hol.gr PARTNERS IBERINSA Coordinator ES EPSILON Contractor GR SOFTWARE AG Contractor IT

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fomfis
FOMFIS

Forest Fire Management and Fire Prevention System

D. Kallidromitou

Managing Director

Epsilon International SA

Monemvasias 27, 151 25 Marousi

Athens-Greece

e-mail: epsilon@hol.gr

partners
PARTNERS
  • IBERINSA Coordinator ES
  • EPSILON Contractor GR
  • SOFTWARE AG Contractor IT
  • IBERSAT Contractor ES
  • SEMA GROUP Contractor ES
  • SESFOR Contractor ES
  • CONAG Contractor ES
  • CPFA Contractor FR
  • NAGREF Contractor GR
what is fomfis
WHAT IS FOMFIS
  • A Tool for
    • Evaluating Fire Prevention
    • Optimising Fighting Strategies
    • Improve Fire Fighting Planning
research areas
RESEARCH AREAS
  • Forest fuel mapping
  • Socio-economic risk analysis
  • Forest fire behaviour simulation
  • Probabilistic planning
technological areas
TECHNOLOGICAL AREAS
  • Remote sensing & automated cartography
  • Geographical information systems
  • Knowledge based systems
  • Fire behaviour simulation
  • Statistical and probabilistic analysis
  • Data & user interfaces software engineering
  • Risk analysis
fomfis modules
FOMFIS MODULES
  • Socio-economic Risk
  • Fuel Mapping
  • Integral Risk
  • Probabilistic Scenarios Generation
  • Fire Behavior Model
  • Efficiency Driven Planning
  • Planning Analysis Engine
  • Reporting
socioeconomic risk
SOCIOECONOMIC RISK

COMPONENTS

SRM

Economic

Social

Demographic

Number of fires

Organisational

socioeconomic risk10
SOCIOECONOMIC RISK
  • Social component data
    • Tourist data
      • Greeks tourists
      • Foreign tourists
    • Land use
      • agricultural
      • grazing land
      • urban
      • rocky
      • wet areas
    • Forested Area (Ha) per Nomos and
    • Industrial Use
socioeconomic risk11
SOCIOECONOMIC RISK
  • Organisational component data
    • Annual expenses:
      • in forest development
      • in forest environmental policy and forest
      • fire protection
      • in forest fire-fighting
    • Personnel :
      • Permanent
      • Temporary
fuel mapping
FUEL MAPPING
  • Multispectral Maximum-Likelihood Classifier of:
    • Landsat-TM Image Bands and
    • A number of auxiliary bands
      • texture extracted from SPOT-PAN
      • elevation
      • slope
  • 18 test sites in the area of Limni
    • Fuel types of the site
    • Position by GPS
fuel mapping15
FUEL MAPPING

BurnedArea

Satellite imagery &

auxiliary data integration

Fuel Loads derived for Evia Island

integral risk model
INTEGRAL RISK MODEL

Physical Risk Map

Compute Physical

Risk

Input Data

Transformation tables

Compute Fire

Appearance

Input Data

Socio-economic RiskNatural risk

Input Data

Fire Appearance

Compute Potential

Damage

Compute Integral

Risk

Potential Damage Map

Integral Risk Map

probabilistic scenarios generation
PROBABILISTIC SCENARIOS GENERATION
  • Allows the user to generate the fires that will appear in the simulation in two ways:
    • Probabilistic Generation.

A set of fires is generated

      • for each meteorological situation in the scenario
      • based on the data extracted from the FAR (Fire Appearance Risk) Map.
    • Random Generation.

A given number of Fires are generated in a random geographical situation

probabilistic scenarios generation18
PROBABILISTIC SCENARIOS GENERATION

Area

Definition

General Data

Definition

Meteorological

Evolution

Definition

Fires

Generation

Wind

Evolution

Definition

fire behavior model
FIRE BEHAVIOR MODEL
  • General Purpose
    • Estimate the fire spread perimeter, area and shape
  • Objectives
    • Calculate the fire importance.
    • Give support to fire fighting dispatching.
    • Calculate extinction costs.
    • Estimate losses and prejudices due to fire action.
    • Obtain the potential spread rate for an EGU for integral risk calculations.
fire behavior model20
FIRE BEHAVIOR MODEL
  • Based on Rothermel’s equation
  • Depends on the fuel model
  • Slope and wind are considered
efficiency driven planning
EFFICIENCY DRIVEN PLANNING
  • General Purpose
    • Allow user to make resources planning according their efficiency in fire vigilance and extinction operations.
  • Objectives
    • Obtain access maps over the analysis area.
    • Calculate access coverage either by airborne and ground fire fighting resources.
    • Estimate visual coverage for vigilance purposes based on the viewshed calculation.
    • Estimate the relationship between work costs and access improvement of the road network.
efficiency driven planning ground total access cost map
EFFICIENCY DRIVEN PLANNINGGround Total Access Cost Map

RASTERIZE ROAD

READS THE FUEL MODEL

NETWORK LAYER

OF EACH EGU

ASSIGNS AN AVERAGE

ASSIGNS AN AVERAGE

S

S

SPEED

ACCORDING

SPEED

ACCORDING

avR

avC

THE ROAD TYPE AND

THE FUEL TYPE AND

TERRAIN SLOPE

TERRAIN SLOPE

CALCULATES THE

CALCULATES THE

TRANSPORT TIME

TRANSPORT TIME

T

=L?60 / S

?1000

T

=L?60 / S

?1000

tR

avR

tC

avC

Depending on the analysis this

ACTUAL VEHICLE

OVERLAPS THE TWO

position regards the base, a

GEOGRAPHICAL

RESULTING MAPS

water point or any other point

POSITION

T

=MIN(

T

,

T

)

coordinates.

t

tR

tC

Access of ground based forces

is calculated through the

existing road network map.

Airborne forces access is

estimated depending on their

average flight speed.

AIRBORNE VEHICLES

GROUND VEHICLES

CALCULATE DISTANCE

IMAP

d FROM ACTUAL TO EGU

Average

Speed S

TOTAL ACCUMULATED

AV

ACCESS TIME

AUTOMATA

CALCULATE ACCESS

CALCULATION

TIME

t=d / S

AV

TCMAP

efficiency driven planning lookouts allocation
EFFICIENCY DRIVEN PLANNINGLookouts Allocation

The viewshed calculation is

obtained from the DTM, but

further detailed analysis will

consider vegetation coverage

height as well.

planning analysis engine
PLANNING ANALYSIS ENGINE

To bring face to face a specific scenario against a proposed planning scheme along a period of time.

Main tasks accomplished are:

  • Classify and characterise fires.
  • Determine number and type of required resources.
  • Effectively assign resources.
  • Compute associated costs of fire fighting operations.
planning analysis engine26
PLANNING ANALYSIS ENGINE
  • Planning Simulation Loop:
    • Update Times: simulation elapsed time increment
    • Update Configuration
    • Update Environment
    • Update resources situation following the transition state diagram:

REFUELING

Autonomy

Refuel End

Dispatch

TRANSPORT(F)

Fire Arrival

READY

FIGHT

PAUSE

Max Work

TRANSPORT(B)

Fight_End

Base Arrival

reporting tool
REPORTING TOOL
  • Results of simulation are presented in form of tables and graphics. They include
    • weather and wind pattern evolution
    • fire outbreaks distribution
    • fire growth average values such as
      • size,
      • fire line intensities,
      • fire importance etc;
  • reports are obtained regarding
    • resources usage
    • dispatching
    • efficiency
reporting tool28
REPORTING TOOL
  • The final evaluation allow planners to identify which strategies could have deeper impact in the final results, comparing
    • costs
    • efficiencies
    • losses
slide29

Thank You

For Your Attention