Towards a European Forest Fire Simulator

Towards a European Forest Fire Simulator J.M. Baetens Research Unit Knowledge-based Systems Ghent University COST Green Engineering Camp July 2, 2012 KERMIT J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 1 / 30

Prologue KERMIT: Knowledge Extraction, Representation and Management using Intelligent Techniques three highly interwoven research threads: knowledge-based modelling predictive modelling spatio-temporal modelling with emphasis on mathematical and computational aspects of relational structures modelling of imprecision and uncertainty (heuristic) optimization harnessing the power of math for engineering bioscience tools J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 2 / 30

Outline 1 Motivation Passed and present situation Future situation 2 Existing information platforms 3 Deployment Required spatio-temporal data Forest fire model 4 Case study J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 3 / 30

Some facts and figures Motivation Passed and present situation Vast areas of (semi)-natural vegetation devastated February 2008, source: NASA J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 4 / 30

Some facts and figures Motivation Passed and present situation Vast areas of (semi)-natural vegetation devastated August 2008, source: NASA J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 4 / 30

Some facts and figures Motivation Passed and present situation Vast areas of (semi)-natural vegetation devastated Impact on natural and human ecosystems across the world Direct and indirect animal casualties Source of greenhouse gases Human casualties Country Date No Total affected Indonesia Oct-1994 3,000,000 Macedonia FRY Jul-2007 1,000,000 United States Oct-2007 640,064 Argentina Jan-1987 152,752 Portugal Jan-2003 150,000 Source: The International Disaster Database (EM-DAT) J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 5 / 30

Some facts and figures Motivation Passed and present situation Vast areas of (semi)-natural vegetation devastated Impact on natural and human ecosystems across the world Direct and indirect animal casualties Source of greenhouse gases Human casualties Economic losses Country Date Damage (US 10 3 $) Indonesia Sep-1997 8,000,000 Canada Jan-1989 4,200,000 United States Oct-2003 3,500,000 United States Oct-1991 2,500,000 United States Oct-2007 2,500,000 Source: The International Disaster Database (EM-DAT) J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 6 / 30

Motivation Passed and present situation Some facts and figures Vast areas of (semi)-natural vegetation devastated Impact on natural and human ecosystems across the world Direct and indirect animal casualties Source of greenhouse gases Human casualties Economic losses Long-lasting Annually in Mediterranean and semi-arid ecosystems Sporadically in (sub)humid climate zones J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 7 / 30

Current hot spots Motivation Passed and present situation Source: NASA J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 8 / 30

Motivation Passed and present situation European situation Most affected states: Portugal, Spain, France, Italy and Greece Other affected countries: Austria, Bulgaria, Croatia, Cyprus, Czech Rep., Estonia, Finland, FYROM, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, Sweden, Switzerland J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 9 / 30

European situation Motivation Passed and present situation Most affected states: Portugal, Spain, France, Italy and Greece Other affected countries: Austria, Bulgaria, Croatia, Cyprus, Czech Rep., Estonia, Finland, FYROM, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, Sweden, Switzerland Portugal Spain France Italy Greece 0.4 Area 10 6 hectares 0.3 0.2 0.1 0.0 1980 1985 1990 1995 2000 2005 2010 Year J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 9 / 30

European situation Motivation Passed and present situation Most affected states: Portugal, Spain, France, Italy and Greece Other affected countries: Austria, Bulgaria, Croatia, Cyprus, Czech Rep., Estonia, Finland, FYROM, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, Sweden, Switzerland Portugal Spain France Italy Greece Other 0.4 Area 10 6 hectares 0.3 0.2 0.1 0.0 1980 1985 1990 1995 2000 2005 2010 Year J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 9 / 30

Motivation Future situation What to expect? Global warming Higher temperatures Less rain in many already affected regions Periodic droughts in more humid climate zones Thus, higher vulnerability of the (semi-)natural environment to the outbreak of wildfires It is of immediate and utter importance to gain insight into the spatio-temporal dynamics of wildfires in order to take adequate management measures for minimizing future losses J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 10 / 30

Outline Existing information platforms 1 Motivation Passed and present situation Future situation 2 Existing information platforms 3 Deployment Required spatio-temporal data Forest fire model 4 Case study J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 11 / 30

Existing information platforms Overview Fire risk maps Current hot spots Fuel maps Extent passed fires No predictions J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 12 / 30

Existing information platforms Overview Fire risk maps Current hot spots Fuel maps Extent passed fires No predictions Source: EFFIS J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 12 / 30

Existing information platforms Overview Fire risk maps Current hot spots Fuel maps Extent passed fires No predictions J.M. Baetens (KERMIT) A European Source: Forest USDA Fire Simulator July 2, 2012 12 / 30

Overview Existing information platforms Fire risk maps Current hot spots Fuel maps Extent passed fires No predictions Fuel class 1 2 3 4 5 6 Perimeter Source: - MODIS Burn Scar Data, USDA Forest 0 9 18 4.5 Kilometers Service Active Fire Mapping Program - Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 12 / 30

Existing information platforms Overview Fire risk maps Current hot spots Fuel maps Extent passed fires No predictions J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 12 / 30

Existing information platforms Data sources Earth observation platforms Terra: MODIS NOAA: AVHRR Landsat GOES SPOT Growing availability Often downloadable Almost real-time Free of charge Source: NASA J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 13 / 30

Existing information platforms Data sources Earth observation platforms Terra: MODIS NOAA: AVHRR Landsat GOES SPOT Growing availability Often downloadable Almost real-time Free of charge Source: NOAA J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 13 / 30

Existing information platforms Data sources Earth observation platforms Terra: MODIS NOAA: AVHRR Landsat GOES SPOT Growing availability Often downloadable Almost real-time Free of charge Source: EFFIS J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 13 / 30

Existing information platforms A European Forest Fire Simulator Supplying the European Forest Fire Information System (EFFIS) with a European Forest Fire Simulator (EFFS) constitutes a logical and beneficial next step in the deployment of a full-fledged environmental information portal in line with the European weather portals: Enables optimized fire fighting and disaster management Informs stakeholders about potential losses and threats Supports the design of appropriate evacuation plans Open to the wide public Creates new opportunities for improving disaster communication J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 14 / 30

Outline Deployment 1 Motivation Passed and present situation Future situation 2 Existing information platforms 3 Deployment Required spatio-temporal data Forest fire model 4 Case study J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 15 / 30

Deployment Required spatio-temporal data Relevant inputs Weather variables Fuel maps Digital elevation model Land cover Vegetation status (NDVI) Soil moisture content Land use Infrastructure Source: Meteo Italia J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 16 / 30

Relevant inputs Deployment Required spatio-temporal data Weather variables Fuel maps Digital elevation model Land cover Vegetation status (NDVI) Soil moisture content Land use Infrastructure Fuel class 1 2 3 4 5 6 Perimeter Source: USDA Source: - MODIS Burn Scar Data, USDA Forest 0 9 18 4.5 Kilometers Service Active Fire Mapping Program - Wildland Fire Science, Earth Resources Observation and Science Center, U.S. Geological Survey J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 16 / 30

Deployment Required spatio-temporal data Relevant inputs Weather variables Fuel maps Digital elevation model Land cover Vegetation status (NDVI) Soil moisture content Land use Infrastructure Source: European Environment Agency J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 16 / 30

Deployment Required spatio-temporal data Relevant inputs Weather variables Fuel maps Digital elevation model Land cover Vegetation status (NDVI) Soil moisture content Land use Infrastructure Source: SPOT-VEGETATION J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 16 / 30

Deployment Required spatio-temporal data Relevant inputs Weather variables Fuel maps Digital elevation model Land cover Vegetation status (NDVI) Soil moisture content Land use Infrastructure Source: European Soil Data Centre J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 16 / 30

Deployment Required spatio-temporal data Relevant inputs Weather variables Fuel maps Digital elevation model Land cover Vegetation status (NDVI) Soil moisture content Land use Infrastructure Source: European Environment Agency J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 16 / 30

Deployment Required spatio-temporal data Requirements Preferably as GIS layers Predictions of weather variables Real-time for rapidly changing inputs Up-to-date for quasi-static inputs High spatial resolution Curated Accessible through the Internet Uniform data format J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 17 / 30

In silico science Deployment Forest fire model Mathematical model A mathematical model is an abstract, simplified, mathematical construct related to a part of reality and created for a particular purpose. Real world Conceptual world Observations Phenomena Modelling Mathematical model Simulating Predictions J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 18 / 30

In silico science Deployment Forest fire model Mathematical model A mathematical model is an abstract, simplified, mathematical construct related to a part of reality and created for a particular purpose. Real world Real time Conceptual world Observations Phenomena Modelling Mathematical model Simulating Predictions J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 18 / 30

Deployment Forest fire model Mathematical modelling 1 Selection of appropriate model structure 2 Model building 3 Calibration 4 Validation 5 EFFIS integration J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 19 / 30

Deployment Forest fire model Selection 1 Selection of appropriate model structure based upon well-defined criteria compatibility with underlying data capability of grasping wildfire dynamics computational efficiency maintenance costs extendability 2 Model building 3 Calibration 4 Validation 5 EFFIS integration J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 20 / 30

Deployment Forest fire model Spectrum of spatio-temporal models state time space D D D... C D D... C C C cellular automaton (CA) coupled-map lattice partial differential equation (PDE) J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 21 / 30

Model building Deployment Forest fire model 1 Selection of appropriate model structure 2 Model building identification of relevant processes and environmental conditions inventory of relevant (geo)databases mathematization of selected processes process coupling implementation in dedicated software establishing links with underlying (geo)databases (weather variables, fuel maps, DEM,...) qualitative assessment of model outcome 3 Calibration 4 Validation 5 EFFIS integration J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 22 / 30

Model building Deployment Forest fire model 1 Selection of appropriate model structure 2 Model building identification of relevant processes and environmental conditions inventory of relevant (geo)databases mathematization of selected processes process coupling implementation in dedicated software establishing links with underlying (geo)databases (weather variables, fuel maps, DEM,...) qualitative assessment of model outcome 3 Calibration 4 Validation 5 EFFIS integration Make everything as simple as possible, but not simpler. Albert Einstein J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 22 / 30

Deployment Forest fire model Model calibration 1 Selection of appropriate model structure 2 Model building 3 Calibration inventory of model parameters sensitivity analysis collection of suitable calibration data sets on the spatio-temporal propagation of European wildfires parameter identification using top-notch optimization procedures to be repeated (partially) as calibration data sets are updated or new ones are gathered 4 Validation 5 EFFIS integration J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 23 / 30

Deployment Forest fire model Model calibration 1 Selection of appropriate model structure 2 Model building 3 Calibration inventory of model parameters sensitivity analysis collection of suitable calibration data sets on the spatio-temporal propagation of European wildfires parameter identification using top-notch optimization procedures to be repeated (partially) as calibration data sets are updated or new ones are gathered 4 Validation 5 EFFIS integration All models are wrong, but some are useful. George Box J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 23 / 30

Deployment Forest fire model Model validation 1 Selection of appropriate model structure 2 Model building 3 Calibration 4 Validation identification of appropriate validation data sets on the spatio-temporal propagation of European wildfires discrimination of suitable discrepancy indices computation of selected discrepancy indices assessment of the model performance feedback to the building stage to be repeated (partially) as calibration data sets are updated or new ones are gathered 5 EFFIS integration J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 24 / 30

EFFIS integration Deployment Forest fire model 1 Selection of appropriate model structure 2 Model building 3 Calibration 4 Validation 5 EFFIS integration coupling EFFIS with involved (geo)-databases design of an user-friendly web interface integration of the EFFS in EFFIS launch of the extended EFFIS public announcement of the improved platform information sessions for dedicated stakeholders J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 25 / 30

Outline Case study 1 Motivation Passed and present situation Future situation 2 Existing information platforms 3 Deployment Required spatio-temporal data Forest fire model 4 Case study J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 26 / 30

Case study Study area Border region Arizona and New Mexico Fuel map available (USDA) 13 classes, 8 in study area, reclassified to 5 classes Coupled-map lattice Forest fire outbreak at day number 148 Lasted for 30 days Spatio-temporal propagation from MODIS data (500 m resolution) J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 27 / 30

Study area Case study Border region Arizona and New Mexico Fuel map available (USDA) 13 classes, 8 in study area, reclassified to 5 classes Coupled-map lattice V(c i,t +1) = V(c i,t) t ( t 1 α i F(c i,t) c j N M i F(c i,t +1) = F(c i,t) t ( t 1 r +α i V(c i,t) ) + V(c i,t) t α j O ij F(c j,t), c j N M i B(c i,t +1) = B(c i,t)+r tf(c i,t), ) α j O ij F(c j,t), Forest fire outbreak at day number 148 Lasted for 30 days Spatio-temporal propagation from MODIS data (500 m resolution) J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 27 / 30

In silico experiment Case study 0 5 10 20 Kilometers Perimeter burnt area Day 148 J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 28 / 30

In silico experiment Case study Perimeter burnt area Point of ignition Registered burnt area Simulated burnt area 0 5 10 20 Day 152 J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 28 / 30

In silico experiment Case study Perimeter burnt area Point of ignition Registered burnt area Simulated burnt area 0 5 10 20 Day 156 J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 28 / 30

In silico experiment Case study Perimeter burnt area Point of ignition Registered burnt area Simulated burnt area 0 5 10 20 Day 162 J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 28 / 30

In silico experiment Case study Perimeter burnt area Point of ignition Registered burnt area Simulated burnt area 0 5 10 20 Day 166 J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 28 / 30

Case study Project team KERMIT (Ghent University) Jan Baetens Bernard De Baets Expertise: GIS Predictive modelling Spatio-temporal modelling FORSIT (Ghent University) Frieke Van Coillie Rob De Wulf Expertise: GIS Forestry Remote sensing J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 29 / 30

Case study J.M. Baetens (KERMIT) A European Forest Fire Simulator July 2, 2012 30 / 30