COMPUTER MODELLING OF WILDLAND-URBAN INTERFACE FIRES

Wildland-urban interface (WUI) fires predominantly originate in wildland fuels and subsequently spread through a spatially heterogeneous and non-contiguous fuel system of structures and residential and wildland vegetation. Commonly used wildland fire models were not developed to handle this complex fuel system. Also, there has been very little activity in the research community to develop data collection methods that capture WUI fuel types and their spatial variation over community scales. For example, the spatial variation of vegetative WUI fuels is often below the resolution (~30 m) of satellite based LANDFIRE wildland fuel maps. In this conference paper, an overview of the use remote sensing data for mapping WUI characteristics will be presented. Specific examples for two WUI communities will be given. The resulting dataset is used to create input files, via a GIS application, for the wildland-urban interface fire dynamics simulator (WFDS). Results from WFDS, applied to a number of settings, are given to illustrate its use in these communities and for exploring risk reduction via wildland fuel treatments.

[1]  Glenn P. Forney,et al.  User's Guide for Smokeview Version 3.1 - A Tool for Visualizing Fire Dynamics Simulation Data , 2000 .

[2]  Dominique Morvan,et al.  Physical modelling of fire spread in Grasslands , 2009 .

[3]  Ian R. Noble,et al.  McArthur's fire-danger meters expressed as equations , 1980 .

[4]  Jie Shan,et al.  Quality of Building Extraction from IKONOS Imagery , 2005 .

[5]  Jesse S. Lozano,et al.  An Investigation of Crown Fuel Bulk Density Effects on the Dynamics of Crown Fire Initiation in Shrublands , 2008 .

[6]  Lara A. Arroyo,et al.  Fire models and methods to map fuel types: The role of remote sensing , 2008 .

[7]  I. Dowman,et al.  Building Extraction using Lidar DEMs and Ikonos Images , 2003 .

[8]  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..

[9]  Glenn P. Forney,et al.  Fire Dynamics Simulator (Version 2) -- Technical Reference Guide | NIST , 2001 .

[10]  Dirk LEMP,et al.  Use of hyperspectral and laser scanning data for the characterization of surfaces in urban areas , 2004 .

[11]  J. Shan,et al.  Building boundary tracing and regularization from airborne lidar point clouds , 2007 .

[12]  I. Burke,et al.  Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests , 2005 .

[13]  Sorin C. Popescu,et al.  Mapping surface fuel models using lidar and multispectral data fusion for fire behavior , 2008 .

[14]  Janice L. Coen,et al.  Simulation of the Big Elk Fire using coupled atmosphere–fire modeling , 2005 .

[15]  S. Ustin,et al.  Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling , 2003 .

[16]  William Mell,et al.  Modeling the spatial distribution of forest crown biomass and effects on fire behavior with FUEL3D and WFDS , 2010 .

[17]  W. Cohen,et al.  Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery , 1992 .

[18]  Russell A. Parsons,et al.  Numerical simulation of crown fire hazard following bark beetle-caused mortality in lodgepole pine forests , 2010 .

[19]  S. Popescu,et al.  A voxel-based lidar method for estimating crown base height for deciduous and pine trees , 2008 .

[20]  M. Flood,et al.  Commercial implications of topographic terrain mapping using scanning airborne laser radar , 1997 .

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

[22]  Laura Chasmer,et al.  Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar , 2006 .

[23]  Hong-Gyoo Sohn,et al.  3-D building extraction using IKONOS multispectral images , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[24]  Ross A. Hill,et al.  Mapping woodland species composition and structure using airborne spectral and LiDAR data , 2005 .

[25]  W. Mell,et al.  A physics-based approach to modelling grassland fires , 2007 .

[26]  S. Reutebuch,et al.  Estimating forest canopy fuel parameters using LIDAR data , 2005 .

[27]  Glenn P. Forney,et al.  User's Guide for Smokeview Version 5: A Tool for Visualizing Fire Dynamics Simulation Data (NIST SP 1017-1) | NIST , 2007 .

[28]  R. Bruce Irvin,et al.  Methods For Exploiting The Relationship Between Buildings And Their Shadows In Aerial Imagery , 1989, Photonics West - Lasers and Applications in Science and Engineering.

[29]  Claus Brenner,et al.  Extraction of buildings and trees in urban environments , 1999 .

[30]  Nicholas Skowronski,et al.  Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey , 2007 .

[31]  Samuel L. Manzello,et al.  Numerical simulation and experiments of burning douglas fir trees , 2009 .

[32]  Jack D. Cohen,et al.  Relating flame radiation to home ignition using modeling and experimental crown fires , 2004 .

[33]  Jack D. Cohen,et al.  Home destruction examination: Grass Valley Fire, Lake Arrowhead, California , 2008 .

[34]  Patricia L. Andrews,et al.  BehavePlus fire modeling system: Past, present, and future , 2007 .

[35]  J. Holmgren,et al.  Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning , 2003, Forest Science.

[36]  Mary Ann Jenkins,et al.  The importance of fire–atmosphere coupling and boundary-layer turbulence to wildfire spread , 2009 .

[37]  Jack D. Cohen,et al.  Structure ignition assessment model (SIAM) , 1995 .

[38]  Marcel Worring,et al.  NIST Special Publication , 2005 .

[39]  M. Maltamo,et al.  The k-MSN method for the prediction of species-specific stand attributes using airborne laser scanning and aerial photographs , 2007 .

[40]  May Yuan,et al.  Assessing Spatial Uncertainty of Lidar-derived Building Model : A Case Study in Downtown Oklahoma City , 2009 .

[41]  P. Treitz,et al.  Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar: an examination of scanning density , 2006 .

[42]  R. Keane,et al.  Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling , 2001 .

[43]  S. Ustin,et al.  Generation of crown bulk density for Pinus sylvestris L. from lidar , 2004 .