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1 (2012) P208 A ( ;2. ( ) ; ) : : (FSI) (NWDI) (PDI) GIS ~ : ; ; (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 : ( ) (1.Yantai Institute of Coastal Zone Research Institute CAS Yantai China; 2. China huangbaohua78@ Agriculture University(Yantai) Yantai China; 3. Land and Resources Bureau of Yantai 126.com Yantai China) : 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 : GIS

2 hm % % 27.3% 17.3% 71 1 [6] hm GIS RS ~2005 Tab.1 The analysis on the cause of fires from 2000 to FSI= Q -Q igavg ig! ( Q " 100 igavg (3) ) Qig (T 0 ) (FMC m%) FSI ()20 1) 20% (373 K ) ; 2) ; 3) [7] : Qig= T T 02 - T m 0 (FRI) (1-e-0.151m ) m : (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 : No. 3 GEOMATICS WORLD 41

3 W L =0.4W D = KJ kg -1 [8] : MODIS WDI=(R/20)+((29-T)/10) (5) -30 C~ [5] : R (%);T +30 C 20 C ( C) 2 Angstrom 20%~80% %; 0%~20% ; : 10% NWDI=100 (2.5-WDI)/(WDI max -WDI min ) KJ kg -1 Angstrom (6) Tab.2 2 Angstrom Angstrom index forest fire-danger weather grading ; [10] MODIS % ~ ~9 MODIS ETM DEM 2.2 [9] : Lgy= lgx (7) MODIS 22 :y ;x 31 ( ) : (NDVI) Fig.1 The vegetation fire potential index at fire spot on June

4 6 5 NDWI NDWI 23 2~6 9~ WDINWDI 2 3 Fig.2 Temperature change curve in Shandong Province Fig.3 Relative humidity change curve in Shandong Province WDI Fig.4 WDI fire danger index at fire spot on June NWDI Fig.5 NWDI fire danger index at fire spot on June ( 6 63% ) ( 7 ) 2000~ ~ Fig.6 Distribution of fire emergency in Shandong Province Fig.7 The population fire probability index map from 2000 to ( 3 9 ) FRI ~120 85~ FRI V No. 3 GEOMATICS WORLD 43

5 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~ ~11 4~1 6~ ~ %; % FRI Fig.10 The FRI index map on January FRI Fig.11 The FRI index map on April FRI Fig.12 The FRI index map on June FRI Fig.13 The FRI index map on October

6 Tab.4 4 FRI The location of FRI value of fire spot 3 3S FRI (RS)GIS No. 3 GEOMATICS WORLD 45

7 [2]Axnparo AB.Oscar FR. An intelligent system for forest firerisk prediction and : fire fighting man agement in Galicia [J]. Exp SystAppl (6): [J]. 2006(1):17~20. [7]. [3]Chuvieco E. and Salas J. Mapping the [J] spatial distribution of forest firedanger (5):99~104. ; using GIS [J]. International Journal of [8]Arpaci Alexander Vacik Harald Formayer Geographical InformationSystems 1996 Herbert A collection of possible ; (10): Fire Weather Indices (FWI) for alpine [4]Maselli F.; Romanelli S.; Bottai L.; landscapes. Zipoli G. Use of NOAA-AVHRR NDVI images for the estimation of dynamic fire [9] K Satoh. [J]. risk in Mediterranean areas [J]. Remote (1):1-5. Sensing of Environment 2003 (86): [10] MODIS FPI-NDVI [5]. MODIS [J] [1]. GIS RS (FPI) [J]. (2): [J] (3): (2): [6]. ( 39 ) : 2 Worboys M.. Foundations of Geographic Information Science [M]. New York: Taylor & Francis [2] [R]. : [3]. ( ) [R]. : : [4]. [J] (6): [5]. [J]. 2010(10): [6]. [J] (1): : [7]. [J]. 2001(10): [8]. : [J] (4): [9]. [J]. 2005(8): [1]Duckham M. Goodchild M.F. and

% GIS / / Fig. 1 Characteristics of flood disaster variation in suburbs of Shang

% GIS / / Fig. 1 Characteristics of flood disaster variation in suburbs of Shang 20 6 2011 12 JOURNAL OF NATURAL DISASTERS Vol. 20 No. 6 Dec. 2011 1004-4574 2011 06-0094 - 05 200062 1949-1990 1949 1977 0. 8 0. 03345 0. 01243 30 100 P426. 616 A Risk analysis of flood disaster in Shanghai