1672-1589(2012)03-0040-07 P208 A 123 1 3 1 1 (1. 264003;2. ( ) 264670;3. 264003) : : (FSI) (NWDI) (PDI) GIS 2010 10 ~2011 9 : ; ; (1977- ) A Study on For est Fir e For ecast Method - Taking Shandong Pr ovince as an example HUANG Bao-hua 123 SUN Zhi-jun 1 ZHOU Li-xia 3 SHI shu-yi 1 MA Yu-qiang 1 : (2009163) (1.Yantai Institute of Coastal Zone Research Institute CAS Yantai 264003 China; 2. China E-mail:huangbaohua78@ Agriculture University(Yantai) Yantai 264670 China; 3. Land and Resources Bureau of Yantai 126.com Yantai 264003 China) :2012-03-10 Abstr act:fuel moisture air temperature relative humidity density of population are important factors in forest fire forecast. These factors construct a comprehensive fire danger index model the model includes three components: vegetation fire sensitivity index (FSI) normalized weather index (NWDI) population fire probability index (PDI ). This paper detailedly introduced the calculation method of various parts of the model integrated the model remote sensing and GIS developed the comprehensive forest fire danger index forecasting system produced the Shandong Province comprehensive fire danger index map from October 2010 to September 2011 and compared to the actual fire. The results show that the model can achieve better prediction results. Key wor ds:fire potential index; normalized weather index; population fire probability index 0 [23] ; [45] ; (RS)GIS ; [1] GIS 1 1.1 : GIS 2000 40
227.4 10 4 hm 2 73 210 662 450 21% 2000-2005 33.4% 27.3% 17.3% 71 1 [6] 16 47.4 10 4 hm 2 84 2000-2005 1.2 26 GIS RS 1 2000~2005 Tab.1 The analysis on the cause of fires from 2000 to 2005 1.2.1 FSI= Q -Q igavg ig! ( Q " 100 igavg (3) ) Qig (T 0 ) (FMC m%) FSI ()20 1) 20% (373 K ) ; 2) ; 3) [7] : Qig=605.03-1.113T 0-0.00243T 02 - T m 0 (FRI) 100 +77.62 (1-e-0.151m )+26.7955m : (2) FSI=FSI L W L +FSI D W D (4) FRI=FSI+NWDI+PDI (1) :T 0 ( )m FSI :FSI ; (%) NWDI ; FSI L FSI D PDI : 2012. 06 No. 3 GEOMATICS WORLD 41
W L =0.4W D =0.6 1514.87 KJ kg -1 [8] : MODIS WDI=(R/20)+((29-T)/10) (5) -30 C~ [5] : R (%);T +30 C 20 C 1.2.2 ( C) 2 Angstrom 20%~80% 2.5 32%; 0%~20% ; : 10% NWDI=100 (2.5-WDI)/(WDI max -WDI min ) 908.238 KJ kg -1 Angstrom (6) Tab.2 2 Angstrom Angstrom index forest fire-danger weather grading 1.2.3 ; [10] 2.3 2011 MODIS 2 1 2011 6 2.1 2 98% 2010 10~12 2012 1~9 MODIS ETM DEM 2.2 [9] : Lgy=-2.71+ 0.64 lgx (7) MODIS 22 :y ;x 31 ( ) 1 2011 6 5 : (NDVI) Fig.1 The vegetation fire potential index at fire spot on June 5 2011 42
6 5 NDWI NDWI 23 2~6 9~11 45 2011 6 2 WDINWDI 2 3 Fig.2 Temperature change curve in Shandong Province Fig.3 Relative humidity change curve in Shandong Province 4 2011 6 5 WDI Fig.4 WDI fire danger index at fire spot on June 5 2011 5 2011 6 5 NWDI Fig.5 NWDI fire danger index at fire spot on June 5 2011 ( 6 63% ) ( 7 ) 2000~2005 6 2000~2005 7 Fig.6 Distribution of fire emergency in Shandong Province Fig.7 The population fire probability index map from 2000 to 2005 2.4 ( 3 9 ) FRI 1995 12 1 75~120 85~100 8 2011 6 2 FRI V 2012. 06 No. 3 GEOMATICS WORLD 43
Tab.3 3 Forest fire-danger grading in Shandong Province 8 Fig.8 The comprehensive fire-danger grading map in Shandong Province 9 FRI Fig.9 The distribution map of fire spot FRI value MODIS I 10~13 2010 10 5 2011 41 39 2011 1~11 4~1 6~2 2010 6 2 10~5 1631 4 95.12%; 2011 6 2 2010 10 5 4.88% 2011 10 2011 1 11 FRI Fig.10 The FRI index map on January 11 2011 11 2011 4 1 FRI Fig.11 The FRI index map on April 1 2011 12 2011 6 2 FRI Fig.12 The FRI index map on June 2 2011 13 2010 10 5 FRI Fig.13 The FRI index map on October 5 2011 44
Tab.4 4 FRI The location of FRI value of fire spot 3 3S FRI (RS)GIS 2012. 06 No. 3 GEOMATICS WORLD 45
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