From: cffdrs: an R package for the Canadian Forest Fire Danger Rating System

(a) Standard FWI System with wintering DC adjustment | (b) Raster-based hourly FFMC | (c) Fire behavior prediction based on results from (b) |
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#Load test data for wDC: data ("test_wDC") #Keep the first weather station, which #is from Penticton, BC, Canada. The #data contains two complete years’ #weather records between 2013 and #2014. dat <- test_wDC[test_wDC$id==1,] #Calculate the fire season start #and end dates: fs <- fireSeason (dat) #Calculate the FWI System #variables for the first year with #standard initial start values. #First, we need to subset the #input data by the start and end #of the fire season in the first year: dat$date <- as.Date (as.POSIXlt (paste (dat$yr,dat$mon,dat$day,sep="-"))) fs$date<- as.Date (as.POSIXlt (paste (fs$yr,fs$mon,fs$day,sep="-"))) curYr <- subset(dat,date>=fs$date[1]&date<=fs$date[2]) #Use of the fwi function is very #straightforward: curYr.fwi<-fwi (curYr) #Calculate the FWI System #variables for the second year #with overwintering modified DC. #This may take a few steps to #accomplish. First, we need to #subset the overwinter period from #this two year weather #observations: winT<-subset (dat,date>fs$date[2]&date<fs$date[3]) #Overwintering DC can then be #calculated easily with wDC function: init.DC<-wDC (curYr.fwi$DC[nrow (curYr.fwi)],sum (winT$prec)) #Second, extract the second fire #season data: secYr<-subset (dat,date>=fs$date[3]&date<=fs$date[4]) #The second year FWI System could #be calculated with the overwintering #DC as the following: secYr.fwi<-fwi (secYr,c (85,6,init.DC)) #To show the difference, we also #calculated the FWI System variables #based on the default initial values: secYr.fwi.default<-fwi (secYr) #We then plotted the 3 outputs that #are affected by the overwintering DC #adjustment, i.e. DC, BUI, and FWI, to #show the difference it makes: x11 (width=12, height=4) par (mfrow=c (1,3), mar=c (5,5,2,1)) plot(secYr.fwi.default$DC,secYr.fwi$DC,pch=19,col='grey50',ylim=c (0,850),xlab="",ylab="With wintering DC",cex.lab=2.0,cex.axis=1.5) abline (0,1,lwd=1.5,lty=2) text (100,800,"DC",cex=2) plot (secYr.fwi.default$BUI,secYr.fwi$BUI,pch=19,col='grey50',xlab="Without wintering DC",ylab="",cex.lab=2.0,cex.axis=1.5) abline (0,1,lwd=1.5,lty=2) text (28,185,"BUI",cex=2) plot (secYr.fwi.default$FWI,secYr.fwi$FWI,pch=19,col='grey50',xlab="",ylab="",cex.lab=2.0,cex.axis=1.5) abline (0,1,lwd=1.5,lty=2) text (8,59,"FWI",cex=2) |
#Load the test data for the first #hour, namely hour01 (See Fig. 4): data(hour01) #or hour01src <- system.file("extdata","test_rast_hour01.tif",package="cffdrs") hour01 <- stack (hour01src) #Assign names to the layers: names (hour01)<-c ("temp","rh","ws","prec") #We calculate the first hour’s #FFMC with the default initial #FFMC value of 85: hffmc.hour01<-hffmcRaster (hour01) #The FFMC for the second hour is #then calculated based on #the previous hour's FFMC. First, #we load the test data for the #second hour, namely hour02, to R: data ("hour02") hour02src <- system.file("extdata","test_rast_hour02.tif",package="cffdrs") hour02 <- stack (hour02src) #Assign variable names to the #layers: names (hour02)<-c ("temp","rh","ws","prec") #The calculation of the second #hour FFMC is slightly different: hffmc.hour02<-hffmcRaster (hour02,ffmc_old=hffmc.hour01) #Map both the inputs and outputs #with a plot function from the #raster package: x11 (width=5, height=6.2) plot (hour02) #First, make a copy of the study area: bui<-hour02$temp #Assign the BUI value: values (bui) <-50 #Rename the layer: names(bui) <- "bui" #Make it into the stack, which can #be used as input in the #hffmcRaster function. hour02<-stack (hour02,bui=bui) #Now we can calculate all hourly #FWI System variables and plot #them: hfwi.hour02<-hffmcRaster (hour02,ffmc_old=hffmc.hour01,hourlyFWI=TRUE) x11 (width=5, height=6.2) plot (hfwi.hour02) |
#First, we calculate the hourly #FFMC with hffmc function. We #convert our raster inputs into a #data.frame first: hffmc.hour01<-as.data.frame (rasterToPoints (hour01)) #The fbp function requires the #coordinates being labeled as #"long" and "lat": names (hffmc.hour01) [1:2]<-c ("long","lat") #Hourly FFMC as inputs for fbp (note #this is a 'multiple weather stations #at one time step' situation): hffmc.hour01$ffmc<-hffmc (hffmc.hour01,batch=FALSE) #Alternatively, this could be done #with hffmcRaster: r<-hffmcRaster (hour01) hffmc.hour01$ffmc<-rasterToPoints (r) [,3] ## Add fuel type and unique ID hffmc.hour01$id<-1:nrow (hffmc.hour01) hffmc.hour01$fuelType<-"C-2" #The new variable that was added #to hffmc.hour01 is named as #'ffmc', which is required by the #fbp function. #Calculate the FBP System (primary #outputs) with all other default #factors: FBP<-fbp (hffmc.hour01) #We can then map a few key fire #behavior measurements from the #outputs: Head Fire Intensity #(HFI), Equilibrium Head Fire Rate #of Spread (ROS), and Total Fuel #Consumption (TFC). HFI<-rasterize (as.matrix(hffmc.hour01[,c ("long","lat")]),r,FBP$HFI) ROS<-rasterize (as.matrix(hffmc.hour01[,c ("long","lat")]),r,FBP$ROS) TFC<-rasterize (as.matrix(hffmc.hour01[,c ("long","lat")]),r,FBP$TFC) #Plot them out: x11 (width=10, height=5.3) par (mfrow=c (1,3), mar=c (5,3.5,5,4)) brks <- seq (0, 1, by=0.1) nb <- length (brks)-1 cols <- rev (heat.colors(nb)) plot (HFI,col=cols,main="Head Fire Intensity (HFI)",cex.main=1.8) plot (ROS,col=cols,main="Rate of Spread (ROS)",cex.main=1.8) plot (TFC,col=cols,main="Total Fuel Consumption (TFC)",cex.main=1.8) # using fpbRaster function, it is # much simplified: ffmc<-hffmcRaster(hour01) ws<-hour01$ws fuel<-ffmc # create a fuel layer fuel[]<-2 # for C-2 fuel type r<-stack (ffmc,fuel,ws) names(r)<-c ("ffmc","fueltype","ws") FBP<-fbpRaster (r) # Plot them: x11 (width=10, height=5.3) par(mfrow=c (1,3), mar=c (5,3.5,5,4)) brks <- seq (0, 1, by=0.1) nb <- length (brks)-1 cols <- rev (heat.colors(nb)) plot (FBP$HFI,col=cols,main="Head Fire Intensity (HFI)",cex.main=1.8) plot (FBP$ROS,col=cols,main="Rate of Spread (ROS)",cex.main=1.8) plot (FBP$TFC,col=cols,main="Total Fuel Consumption (TFC)",cex.main=1.8) |