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FOMFIS

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

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  1. 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

  2. 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

  3. WHAT IS FOMFIS • A Tool for • Evaluating Fire Prevention • Optimising Fighting Strategies • Improve Fire Fighting Planning

  4. RESEARCH AREAS • Forest fuel mapping • Socio-economic risk analysis • Forest fire behaviour simulation • Probabilistic planning

  5. 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

  6. TEST AREAS

  7. FOMFIS ARCHITECTURE

  8. FOMFIS MODULES • Socio-economic Risk • Fuel Mapping • Integral Risk • Probabilistic Scenarios Generation • Fire Behavior Model • Efficiency Driven Planning • Planning Analysis Engine • Reporting

  9. SOCIOECONOMIC RISK COMPONENTS SRM Economic Social Demographic Number of fires Organisational

  10. 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

  11. 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

  12. SOCIOECONOMIC RISK S R M

  13. 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

  14. FUEL MAPPING Sampling Test Sites

  15. FUEL MAPPING BurnedArea Satellite imagery & auxiliary data integration Fuel Loads derived for Evia Island

  16. 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

  17. 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

  18. PROBABILISTIC SCENARIOS GENERATION Area Definition General Data Definition Meteorological Evolution Definition Fires Generation Wind Evolution Definition

  19. 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.

  20. FIRE BEHAVIOR MODEL • Based on Rothermel’s equation • Depends on the fuel model • Slope and wind are considered

  21. 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.

  22. 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

  23. EFFICIENCY DRIVEN PLANNINGBases & Water Points Allocation

  24. EFFICIENCY DRIVEN PLANNINGLookouts Allocation The viewshed calculation is obtained from the DTM, but further detailed analysis will consider vegetation coverage height as well.

  25. 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.

  26. 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

  27. 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

  28. REPORTING TOOL • The final evaluation allow planners to identify which strategies could have deeper impact in the final results, comparing • costs • efficiencies • losses

  29. Thank You For Your Attention

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