1. D. Kallidromitou 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. D. Kallidromitou PARTNERS IBERINSACoordinator ES EPSILONContractorGR SOFTWARE AGContractorIT IBERSATContractorES SEMA GROUPContractorES SESFORContractorES CONAGContractorES CPFAContractorFR NAGREFContractorGR

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

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

5. D. Kallidromitou TECHNOLOGICAL AREAS Remote sensing & automated cartography Remote sensing & automated cartography Geographical information systems Geographical information systems Knowledge based systems Knowledge based systems Fire behaviour simulation Fire behaviour simulation Statistical and probabilistic analysis Statistical and probabilistic analysis Data & user interfaces software engineering Data & user interfaces software engineering Risk analysis Risk analysis

6. D. Kallidromitou TEST AREAS

7. D. Kallidromitou FOMFIS ARCHITECTURE

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

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

10. D. Kallidromitou SOCIOECONOMIC RISK Social component data 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. D. Kallidromitou SOCIOECONOMIC RISK Organisational component data Organisational component data  Annual expenses:  in forest development  in forest environmental policy and forest  fire protection  in forest fire-fighting  Personnel :  Permanent  Temporary

12. D. Kallidromitou SOCIOECONOMIC RISK SRMSRM

13. D. Kallidromitou FUEL MAPPING Multispectral Maximum-Likelihood Classifier of: 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 18 test sites in the area of Limni  Fuel types of the site  Position by GPS

14. D. Kallidromitou Sampling Test Sites FUEL MAPPING

15. D. Kallidromitou FUEL MAPPING Fuel Loads derived for Evia Island Satellite imagery & auxiliary data integration Burned Area

16. D. Kallidromitou INTEGRAL RISK MODEL Input Data Compute Physical Risk Transformation tables Physical Risk Map Compute Fire Appearance Compute Potential Damage Compute Integral Risk Input Data Fire Appearance Integral Risk Map Potential Damage Map Input Data Socio-economic Risk Natural risk

17. D. Kallidromitou PROBABILISTIC SCENARIOS GENERATION Allows the user to generate the fires that will appear in the simulation in two ways: 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. D. Kallidromitou PROBABILISTIC SCENARIOS GENERATION Area Definition General Data Definition Meteorological Evolution Definition Wind Evolution Definition Fires Generation

19. D. Kallidromitou FIRE BEHAVIOR MODEL General Purpose General Purpose  Estimate the fire spread perimeter, area and shape Objectives 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. D. Kallidromitou FIRE BEHAVIOR MODEL Based on Rothermel’s equation Depends on the fuel model Slope and wind are considered

21. D. Kallidromitou EFFICIENCY DRIVEN PLANNING General Purpose General Purpose  Allow user to make resources planning according their efficiency in fire vigilance and extinction operations. Objectives 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. D. Kallidromitou EFFICIENCY DRIVEN PLANNING Ground Total Access Cost Map RASTERIZE ROAD NETWORK LAYER ASSIGNS AN AVERAGE SPEED S avR ACCORDING THE ROAD TYPE AND TERRAIN SLOPE CALCULATES THE TRANSPORT TIME T tR =L?60 / S avR ?1000 READS THE FUEL MODEL OF EACH EGU ASSIGNS AN AVERAGE SPEED S avC ACCORDING THE FUEL TYPE AND TERRAIN SLOPE CALCULATES THE TRANSPORT TIME T tC =L?60 / S avC ?1000 OVERLAPS THE TWO RESULTING MAPS T t =MIN(T tR,T tC ) ACTUAL VEHICLE GEOGRAPHICAL POSITION GROUND VEHICLESAIRBORNE VEHICLES CALCULATE DISTANCE d FROM ACTUAL TO EGU CALCULATE ACCESS TIMEt=d / S AV IMAP TOTAL ACCUMULATED ACCESS TIME AUTOMATA CALCULATION TCMAP AverageSpeed S AV Depending on the analysis this position regards the base, a water point or any other point coordinates. Access of ground based forces is calculated through the existing road network map. Airborne forces access is estimated depending on their average flight speed.

23. D. Kallidromitou EFFICIENCY DRIVEN PLANNING Bases & Water Points Allocation

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

25. D. Kallidromitou 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. D. Kallidromitou PLANNING ANALYSIS ENGINE Planning Simulation Loop: Planning Simulation Loop:  Update Times: simulation elapsed time increment  Update Configuration  Update Environment  Update resources situation following the transition state diagram: Base Arrival Max Work READY TRANSPORT(B) FIGHT REFUELING Dispatch Fight_End Fire Arrival Autonomy PAUSE Refuel End TRANSPORT(F)

27. D. Kallidromitou REPORTING TOOL Results of simulation are presented in form of tables and graphics. They include 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 reports are obtained regarding  resources usage  dispatching  efficiency

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

29. D. Kallidromitou For Your Attention Thank You