Wildfire Risk Assessment in a Typical Mediterranean Wildland–Urban Interface of Greece

The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland–urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source–sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey’s significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.

[1]  James K. Brown,et al.  Handbook for inventorying surface fuels and biomass in the interior West. General technical report , 1982 .

[2]  Luís Bragança,et al.  A methodological approach , 2005 .

[3]  Heike Freud,et al.  Measurements For Terrestrial Vegetation , 2016 .

[4]  E. Chuvieco,et al.  Human-caused wildfire risk rating for prevention planning in Spain. , 2009, Journal of environmental management.

[5]  Matthew P. Thompson,et al.  A Risk-Based Approach to Wildland Fire Budgetary Planning , 2013 .

[6]  Charles W. McHugh,et al.  A simulation study of thinning and fuel treatments on a wildland–urban interface in eastern Oregon, USA , 2007 .

[7]  Matthew P. Thompson,et al.  A Wildfire Risk Assessment Framework for Land and Resource Management , 2013 .

[8]  Charles W. McHugh,et al.  Modeling Containment of Large Wildfires Using Generalized Linear Mixed-Model Analysis , 2009, Forest Science.

[9]  Corinne Lampin-Maillet,et al.  Mapping wildland-urban interfaces at large scales integrating housing density and vegetation aggregation for fire prevention in the South of France. , 2010, Journal of environmental management.

[10]  A. Dimitrakopoulos.  Mediterranean fuel models and potential fire behaviour in Greece. , 2002 .

[11]  A. P. Dimitrakopoulos,et al.  Pyric properties of some dominant Mediterranean vegetation species , 2001 .

[12]  Pierpaolo Duce,et al.  Evaluation of FARSITE simulator in Mediterranean maquis , 2007 .

[13]  Hong S. He,et al.  Comparing fuel reduction treatments for reducing wildfire size and intensity in a boreal forest landscape of northeastern China. , 2013, The Science of the total environment.

[14]  E. Chuvieco,et al.  Development of a framework for fire risk assessment using remote sensing and geographic information system technologies , 2010 .

[15]  G. Richards.  An elliptical growth model of forest fire fronts and its numerical solution , 1990 .

[16]  N. West,et al.  Measurements of Terrestrial Vegetation , 1989 .

[17]  D. C. Le Maitre,et al.  Fire Behaviour in South African Fynbos (Macchia) Vegetation and Predictions from Rothermel's Fire Model , 1985 .

[18]  Charles W. McHugh,et al.  A Method for Ensemble Wildland Fire Simulation , 2011 .

[19]  A. Ager,et al.  Potential changes in fire probability and severity under climate change scenarios in Mediterranean areas , 2012 .

[20]  John Anderson,et al.  ArcFuels10 system overview , 2013 .

[21]  E. Chuvieco,et al.  Integrating geospatial information into fire risk assessment , 2014 .

[22]  A. P. Dimitrakopoulos,et al.  PYROSTAT -- a computer program for forest fire data inventory and analysis in Mediterranean countries , 2001, Environ. Model. Softw..

[23]  Timo Pukkala,et al.  Integrating fire risk considerations in landscape-level forest planning , 2011 .

[24]  I. Mitsopoulos,et al.  Estimation of canopy fuel characteristics of Aleppo pine (Pinus halepensis Mill.) forests in Greece based on common stand parameters , 2013, European Journal of Forest Research.

[25]  Mark A. Finney,et al.  The challenge of quantitative risk analysis for wildland fire , 2005 .

[26]  A. Bachmann,et al.  A consistent wildland fire risk terminology is needed , 2001 .

[27]  H. Preisler,et al.  Analyzing wildfire exposure and source–sink relationships on a fire prone forest landscape , 2012 .

[28]  F. Moreira,et al.  Modeling and mapping wildfire ignition risk in Portugal , 2009 .

[29]  Patricia L. Andrews,et al.  Fuels Management-How to Measure Success: Conference Proceedings , 2006 .

[30]  Yohay Carmel,et al.  Assessing fire risk using Monte Carlo simulations of fire spread , 2009 .

[31]  Patricia L. Andrews,et al.  How to Generate and Interpret Fire Characteristics Charts for Surface and Crown Fire Behavior , 2012 .

[32]  F. Moreira,et al.  Landscape--wildfire interactions in southern Europe: implications for landscape management. , 2011, Journal of environmental management.

[33]  Lisa M. Holsinger,et al.  Climate change effects on historical range and variability of two large landscapes in western Montana, USA , 2008 .

[34]  Matthew P. Thompson,et al.  How risk management can prevent future wildfire disasters in the wildland-urban interface , 2013, Proceedings of the National Academy of Sciences.

[35]  J. Forthofer.  Modeling wind in complex terrain for use in fire spread prediction , 2007 .

[36]  Alan A. Ager,et al.  A review of recent advances in risk analysis for wildfire management , 2013 .

[37]  Raphaele Blanchi,et al.  Forest fire risk assessment and cartography - a methodological approach. , 2002 .

[38]  Isabel Cristina Pascual Castaño,et al.  Fire models and methods to map fuel types: The role of remote sensing. , 2008 .

[39]  Alan A. Ager,et al.  Assessing exposure of human and ecological values to wildfire in Sardinia, Italy , 2013 .

[40]  Joe H. Scott.  An analytical framework for quantifying wildland fire risk and fuel treatment benefit , 2006 .

[41]  J. Greenberg,et al.  Spatial variability in wildfire probability across the western United States , 2012 .

[42]  Volker C. Radeloff,et al.  Wildfire risk in the wildland―urban interface: A simulation study in northwestern Wisconsin , 2009 .

[43]  Matthew P. Thompson,et al.  Assessing Watershed-Wildfire Risks on National Forest System Lands in the Rocky Mountain Region of the United States , 2013 .

[44]  Alan A. Ager,et al.  Measuring the effect of fuel treatments on forest carbon using landscape risk analysis , 2010 .

[45]  C. Hardy.  Wildland fire hazard and risk: Problems, definitions, and context , 2005 .

[46]  Jessica G Turnley,et al.  Predicting risks of uncharacteristic wildfires: Application of the risk assessment process , 2005 .

[47]  Charles W. McHugh,et al.  A comparative risk assessment framework for wildland fire management: the 2010 cohesive strategy science report , 2011 .

[48]  Raul Romero-Calcerrada,et al.  GIS analysis of spatial patterns of human-caused wildfire ignition risk in the SW of Madrid (Central Spain) , 2008, Landscape Ecology.

[49]  Giorgos Mallinis,et al.  Local-Scale Fuel-Type Mapping and Fire Behavior Prediction by Employing High-Resolution Satellite Imagery , 2008, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[50]  M. Finney.  Fire growth using minimum travel time methods , 2002 .

[51]  R. Neil Sampson,et al.  Spatial data for national fire planning and fuel management , 2001 .

[52]  Christos Giannakopoulos,et al.  Sensitivity and evaluation of current fire risk and future projections due to climate change: the case study of Greece , 2013 .

[53]  Faith R. Kearns,et al.  Classification of the wildland-urban interface: A comparison of pixel- and object-based classifications using high-resolution aerial photography , 2008, Comput. Environ. Urban Syst..

[54]  Domingos Xavier Viegas,et al.  Moisture Content of Fine Forest Fuels and Fire Occurrence in Central Portugal , 1992 .

[55]  W. Romme,et al.  Expansion of the US wildland–urban interface , 2007 .

[56]  Donatella Spano,et al.  Analyzing spatiotemporal changes in wildfire regime and exposure across a Mediterranean fire-prone area , 2014, Natural Hazards.

[57]  Alan A. Ager,et al.  Wildfire risk and hazard: procedures for the first approximation , 2010 .

[58]  Kostas Kalabokidis,et al.  Integrating new methods and tools in fire danger rating , 2007 .

[59]  S. L. Manzello,et al.  The wildland-urban interface fire problem - current approaches and research needs , 2010 .

[60]  John Handmer,et al.  Australian bushfire fatalities 1900–2008: exploring trends in relation to the ‘Prepare, stay and defend or leave early’ policy , 2010 .

[61]  Matthew P. Thompson,et al.  Integrated national-scale assessment of wildfire risk to human and ecological values , 2011 .