Finney M A. FARSITE: Fire area simulator–model development and valuation. USDA, Forest Service. Rep. No. Paper RMRS-RP-4. 1998.
[2]
Sandberg D V, Ottmar R D, Cushon G H. Characterizing fuels in the 21st Century. International Journal of Wildland Fire, 2001, 10(3/4): 381-187.
[3]
Ottmar R D, Sandberg D V, Riccardi C L, et al. An overview of the fuel characteristics classification system: Quantifying, classifying, and creating fuelbeds for resource planning. Canadian Journal of Forest Research, 2007, 37(12): 2383-2393.
[4]
Cheney P. A National Fire Danger Rating System for Australia. International Forest Fire News.
[5]
[1992-2-
[6]
Van Wagner C E. Development and Structure of the Canadian Forest Fire Behavior Prediction System. Forestry Canada, Forestry Canada Fire Danger Group. Information Report ST-X-3. 1992.
[7]
Giakoumakis M N, Gitas I Z, San-Miguel J. Object-oriented classification modeling for fuel type mapping in the Mediterranean, using LANDSAT TM and IKONOS imagery preliminary results. Viegas. Forest Fire Research & Wildland Fire Safety. Rotterdam:Millpress, 2002: 1-13.
[8]
Keane R E, Burgan R E, Wagtendonk J V. Mapping wildland fuel for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling. International Journal of Wildland Fire, 2001, 10(4): 301-319.
[9]
van Wagtendonk J W, Root R R. The USE of multitemporal Landsat normalized difference vegetation index (NDVI) data for mapping fuels models in Yosemite National Park, USA. International Journal of Remote Sensing, 2003, 24(3): 1639-1651.
[10]
Lanorte A, Lasaponara R. Fuel type characterization based on coarse resolution MODIS satellite data. Journal of Biogeosciences and Forestry, 2008, 1: 60-64.
[11]
Lefsky M A, Cohen W B, Parker G G, et al. Lidar Remote Sensing for Ecosystem Studies. BioScience, 2002, 52(1): 19-30.
[12]
Austin J M, Mackey B G, Van Niel K P. Estimating forest biomass using satellite radar: an exploratory study in a temperate Australian Eucalyptus forest. Forest Ecology and Management, 2003, 176(1/2/3): 575-583.
[13]
Andersen H E, McGaughey R J, Reutebuch S E. Estimating forest canopy fuel parameters using LIDAR data. Remote Sensing of Environment, 2005, 94(4): 441-449.
[14]
Kalabokidis K, Hay C, Hussin Y. Spatially resolved fire growth simulation//Proceedings of the 11th Conference on Fire and Forest Meterology, 1991: 188-195.
[15]
Vasconcelos M J, Guertin D P. FIREMAP: Simulation of fire growth with a geographic information system. International Journal of Wildland Fire, 1992, 2(2): 87-96.
[16]
Lopes A, Cruz M, Viegas D. Firestation-an integrated software system for the numerical simulation of fire spread on complex topography. Environmental Modelling & Software, 2002, 17(3): 269-285.
[17]
Perry G L, Sparrow A D, Owens I F. A gis-supported model for the simulation of the spatial structure of wildland fire, Cass Basin, New Zealand. Journal of Applied Ecology, 1999, 36(4): 502-518.
[18]
Weise D R, Biging G S. A qualitative comparison of fire spread models incorporating wind and slope effects. Forest Science, 1997, 43(2): 170-180.
[19]
Noble I R, Bary G A V, Gill A M. McArthur's fire-danger meters expressed as equations. Australian Journal of Ecology, 1980, 5(2): 201-203.
[20]
Ensis. SiroFire: A computer-based fire spread simulator
[21]
[EB/OL]
[22]
.
[23]
Cheney N P, Gould J S, Catchpole W R. Prediction of fire spread in grasslands. International Journal of Wildland Fire, 1998, 8(1): 1-13.
[24]
Van Wagner C E, The development and structure of the Canadian Forest Fire Weather Index System. Canadian Forest Service, Petawawa National Forestry Institute. FTR-35. 1987.
[25]
Richards G D. A general mathematical framework for modeling two-dimensional wildfire spread. International Journal of Wildland Fire, 1995, 5(2): 63-72.
[26]
Karafyllidis I, Thanailakis A. A model for predicting forest fire spreading using cellular automata. Ecological Modelling, 1997, 99(1): 87-97.
[27]
Berjak S G, Hearne J W. An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modelling, 2002, 148(2): 133-151.
[28]
Encinas L H, White S H, del Rey A M, et al. Modelling forest fire spread using hexagonal cellular automata. Applied Mathematical Modelling, 2007, 31(6): 1213-1227.
[29]
Alexandridis A, Vakalis D, Siettos C I, et al. A cellular automata model for forest fire spread prediction: The case of the wildfire that swept through Spetses Island in 1990. Applied Mathematics and Computation, 2008, 204(1): 191-201.
[30]
Yassemi S, Dragicevic S, Schmidtb M. Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour. Ecological Modelling, 2008, 210(1/2): 71-84.
[31]
Karafyllidis I, Thanailakis A. Design of a dedicated parallel processor for the prediction of forest fire spreading using cellular automata and genetic algorithms. Engineering Applications of Artificial Intelligence, 2004, 17(1): 19-36.
[32]
Innocenti E, Silvani X, Muzya A, et al. A software framework for fine grain parallelization of cellular models with OpenMP: Application to fire spread. Environmental Modelling & Software, 2009, 24(7): 1-13.
[33]
Richards G D. An elliptical growth model of forest fire fronts and its numerical solution. International Journal for Numerical Methods in Engineering, 1990, 30(6):1163-1179.
Gonzalez-alonso F, Cuevas J M, Casanova J L, et al. A forest fire risk assessment using NOAA AVHRR images in the Valencia area, eastern Spain. International Jounrnal Remote Sensing, 1997, 18(10): 2201-2207.
[51]
Burgan R E, Klaver R W, Klaver J M. Fuel models and fire potential from satellite and surface observation. International Journal of Wildland Fire, 1998, 8(3): 159-170.
[52]
Ana. Integration of satellite sensor data, fuel type maps and meteorological observations for evaluation of forest fire risk at the pan-European scale. International Jounrnal Remote Sensing, 2002, 23(13): 2713-2719.
[53]
Peng G, Li J, Chen Y, et al. A forest fire risk assessment using ASTER images in Peninsular Malaysia. Journal of China University of Mining & Technology, 2007, 17(2): 232-237.
[54]
Jaiswal R K, Mukherjee S, Raju K D, et al. Forest fire risk zone mapping from satellite imagery and GIS. International Journal of Applied Earth Observation and Geoinformation, 2002, 4(1): 1-10.
[55]
Xu D, Dai L M, Shao G F, et al. Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China. Journal of Forestry Research, 2005, 16(3): 169-173.
[56]
Kalabokidis K D, Koutsias N, Konstantinidis P, et al. Multivariate analysis of landscape wildfire dynamics in a Mediterranean ecosystem of Greece. Area, 2007, 39(3): 392-402.
[57]
Martinez J, Garcia C V, Chuvieco E. Human-caused wildfire risk rating for prevention planning in Spain. Journal of Environmental Management, 2009, 90(2): 1241-1252.
[58]
Vasconcelos M J P, Silva S, Tomé M. Spatial prediction of fire ignition probabilities: Comparing logistic regression and neural networks. Photogrammetric Engineering and Remote Sensing, 2001, 67(1): 73-81.
[59]
Carmel Y, Paz b S, Jahashan F, et al. Assessing fire risk using Monte Carlo simulations of fire spread. Forest Ecology and Management, 2009, 257(1): 370-377.
[60]
Tong Z, Zhang J, Liu X. GIS-based risk assessment of grassland fire disaster in western Jilin province, China. Stoch Environ Res Risk Assess, 2009, 23(4): 463-471.
[61]
Chuviecoa E, Aguadoa I, Yebra M, et al. Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, 2009, 221(1): 46-58.
Rothermel R C. A mathematical model for predicting fire spread in wildland fuels. USDA, Forest Service. Rep. No. RP INT-115, 1972.
[64]
Pastor E, Zarate L, Planas E, et al. Mathematical models and calculation systems for the study of wildland fire behaviour. Progress in Energy and Combustion Science, 2003, 29(2): 139-153.
Cohen J D, Deeming J E. The National Fire Danger Rating System: Basic equations. Pacific Southwest Forest and Range Experiment Station. Rep. No. PSW-82, 1982.
[67]
Albini F A. Estimating wildfire behavior and effects. USDA, Forest Service, Intermountain Forest and Range Experiment Station. Rep. No. GTR INT-30, 1976.
[68]
Anderson H E. Aids to determining fuel models for estimating fire behavior. USDA, Forest Service. Rep. No. GTR INT-122, 1982.
[69]
Burgan R E R, Richard C. BEHAVE: Fire behavior prediction and fuel modeling system-FUEL subsystem. USDA, Forest Service, Intermountain Forest and Range Experiment Station. General Technical Report INT-167, 1984.
[70]
Andrews P L. BEHAVE: Fire behavior prediction and fuel modeling system-Burn subsystem, Part 1. USDA, Forest Service, Intermountain Forest and Range Experiment Station. Rep. No. GTR INT-194, 1986.
[71]
Mbow C, Goita K, Benie G. Spectral indices and fire behavior simulation for fire risk assessment in savanna ecosystems. Remote Sensing of Environment, 2004, 91(1):1-13.
