Merged U.S. & Canada Fire-Start Data
1 Merge the US & Canada Fire-start Data
Load the U.S. (merged) & Canada (trimmed) data sets
load("e:/Projects/fire/DailyFireStarts/data/RData/us_1986-2013.RData")
load("e:/Projects/fire/DailyFireStarts/data/RData/can_1986-2013.RData")
options(width=100)str(us_merged)## 'data.frame': 1849052 obs. of 14 variables:
## $ datasource : Factor w/ 2 levels "fpafod","nifc": 1 1 1 1 1 1 1 1 1 1 ...
## $ sourceid : int 1 2 3 4 5 6 7 8 9 10 ...
## $ latitude : num 40 38.9 39 38.6 38.6 ...
## $ longitude : num -121 -120 -121 -120 -120 ...
## $ year : num 2005 2004 2004 2004 2004 ...
## $ mon : num 2 5 5 6 6 6 7 3 3 7 ...
## $ day : num 2 12 31 28 28 30 1 8 15 1 ...
## $ daynum : num 33 133 152 180 180 182 183 67 74 183 ...
## $ area_ha : num 0.0405 0.1012 0.0405 0.0405 0.0405 ...
## $ cause_original: num 9 1 5 1 1 1 1 5 5 1 ...
## $ cause1 : num 2 1 2 1 1 1 1 2 2 1 ...
## $ cause2 : num 8 1 5 1 1 1 1 5 5 1 ...
## $ stateprov : Factor w/ 52 levels "AK","AL","AR",..: 5 5 5 5 5 5 5 5 5 5 ...
## $ agency : Factor w/ 12 levels "BIA","BLM","BOR",..: 6 6 6 6 6 6 6 6 6 6 ...str(can)## 'data.frame': 234813 obs. of 14 variables:
## $ datasource : Factor w/ 1 level "cnfdb": 1 1 1 1 1 1 1 1 1 1 ...
## $ sourceid : int 1 2 3 4 5 6 7 8 9 10 ...
## $ latitude : num 53.3 47.8 47.4 47 49 ...
## $ longitude : num -63.4 -54.5 -52.7 -55.5 -55.7 ...
## $ year : int 1993 1999 1986 1986 1986 1986 1986 1986 1986 1986 ...
## $ mon : int 6 5 5 5 5 5 5 5 5 5 ...
## $ day : int 19 19 16 16 14 15 15 16 16 17 ...
## $ daynum : num 170 139 136 136 134 135 135 136 136 137 ...
## $ area_ha : num 1300 380 731 456 19472 ...
## $ cause_original: num 3 1 1 1 1 1 1 1 1 1 ...
## $ cause1 : num 1 2 2 2 2 2 2 2 2 2 ...
## $ cause2 : num 0 0 0 0 0 0 0 0 0 0 ...
## $ stateprov : Factor w/ 56 levels "AB","BC","MB",..: 5 5 5 5 5 5 5 5 5 5 ...
## $ agency : Factor w/ 56 levels "AB","BC","MB",..: 5 5 5 5 5 5 5 5 5 5 ...summary(us_merged)## datasource sourceid latitude longitude year mon
## fpafod:1727476 Min. : 1 Min. :17.94 Min. :-178.80 Min. :1986 Min. : 1
## nifc : 121576 1st Qu.: 359278 1st Qu.:32.99 1st Qu.:-111.48 1st Qu.:1996 1st Qu.: 4
## Median : 908962 Median :35.62 Median : -92.91 Median :2002 Median : 6
## Mean : 30072960 Mean :37.01 Mean : -96.31 Mean :2002 Mean : 6
## 3rd Qu.: 1663336 3rd Qu.:41.05 3rd Qu.: -82.54 3rd Qu.:2008 3rd Qu.: 8
## Max. :201940182 Max. :70.14 Max. : -65.26 Max. :2013 Max. :12
##
## day daynum area_ha cause_original cause1
## Min. : 1.00 Min. : 1.0 Min. : 0.00 Min. : 0.000 Min. :1.000
## 1st Qu.: 8.00 1st Qu.: 92.0 1st Qu.: 0.04 1st Qu.: 2.000 1st Qu.:2.000
## Median :15.00 Median :170.0 Median : 0.40 Median : 5.000 Median :2.000
## Mean :15.52 Mean :166.9 Mean : 32.24 Mean : 5.728 Mean :1.935
## 3rd Qu.:23.00 3rd Qu.:231.0 3rd Qu.: 1.29 3rd Qu.: 9.000 3rd Qu.:2.000
## Max. :31.00 Max. :366.0 Max. :245622.14 Max. :13.000 Max. :3.000
##
## cause2 stateprov agency
## Min. : 0.000 CA : 196976 ST/C&L :1254551
## 1st Qu.: 3.000 GA : 163298 FS : 206731
## Median : 5.000 TX : 126100 BIA : 128871
## Mean : 5.043 NC : 105113 BLM : 112063
## 3rd Qu.: 8.000 FL : 87589 USFS : 71387
## Max. :10.000 AZ : 79969 NPS : 28050
## (Other):1090007 (Other): 47399summary(can)## datasource sourceid latitude longitude year mon
## cnfdb:234813 Min. : 1 Min. :41.92 Min. :-141.00 Min. :1986 Min. : 1.000
## 1st Qu.: 58704 1st Qu.:49.16 1st Qu.:-120.15 1st Qu.:1992 1st Qu.: 6.000
## Median :117407 Median :50.85 Median :-114.54 Median :1999 Median : 7.000
## Mean :117407 Mean :51.80 Mean :-104.60 Mean :1999 Mean : 6.697
## 3rd Qu.:176110 3rd Qu.:54.59 3rd Qu.: -89.31 3rd Qu.:2007 3rd Qu.: 8.000
## Max. :234813 Max. :69.60 Max. : -52.69 Max. :2013 Max. :12.000
##
## day daynum area_ha cause_original cause1 cause2
## Min. : 1.00 Min. : 1.0 Min. : 0.0 Min. :0.000 Min. :1.00 Min. :0
## 1st Qu.: 8.00 1st Qu.:152.0 1st Qu.: 0.0 1st Qu.:1.000 1st Qu.:1.00 1st Qu.:0
## Median :15.00 Median :193.0 Median : 0.1 Median :1.000 Median :2.00 Median :0
## Mean :15.52 Mean :187.9 Mean : 279.2 Mean :2.046 Mean :1.63 Mean :0
## 3rd Qu.:23.00 3rd Qu.:221.0 3rd Qu.: 0.9 3rd Qu.:3.000 3rd Qu.:2.00 3rd Qu.:0
## Max. :31.00 Max. :366.0 Max. :577646.8 Max. :5.000 Max. :3.00 Max. :0
##
## stateprov agency
## BC :85833 BC :85833
## ON :38875 ON :38875
## AB :33239 AB :33239
## SK :17945 SK :17945
## QC :17180 QC :17180
## MB :11665 MB :11665
## (Other):30076 (Other):30076Make the merged file
uscan <- rbind(us_merged,can)
summary(uscan)## datasource sourceid latitude longitude year
## fpafod:1727476 Min. : 1 Min. :17.94 Min. :-178.80 Min. :1986
## nifc : 121576 1st Qu.: 222557 1st Qu.:33.33 1st Qu.:-113.58 1st Qu.:1996
## cnfdb : 234813 Median : 762762 Median :36.62 Median : -94.14 Median :2002
## Mean : 26697523 Mean :38.68 Mean : -97.25 Mean :2002
## 3rd Qu.: 1456633 3rd Qu.:43.94 3rd Qu.: -82.63 3rd Qu.:2007
## Max. :201940182 Max. :70.14 Max. : -52.69 Max. :2013
##
## mon day daynum area_ha cause_original cause1
## Min. : 1.000 Min. : 1.00 Min. : 1.0 Min. : 0.0 Min. : 0.000 Min. :1.0
## 1st Qu.: 4.000 1st Qu.: 8.00 1st Qu.: 99.0 1st Qu.: 0.0 1st Qu.: 2.000 1st Qu.:2.0
## Median : 6.000 Median :15.00 Median :175.0 Median : 0.3 Median : 5.000 Median :2.0
## Mean : 6.079 Mean :15.52 Mean :169.2 Mean : 60.1 Mean : 5.313 Mean :1.9
## 3rd Qu.: 8.000 3rd Qu.:23.00 3rd Qu.:228.0 3rd Qu.: 1.2 3rd Qu.: 8.000 3rd Qu.:2.0
## Max. :12.000 Max. :31.00 Max. :366.0 Max. :577646.8 Max. :13.000 Max. :3.0
##
## cause2 stateprov agency
## Min. : 0.000 CA : 196976 ST/C&L :1254551
## 1st Qu.: 2.000 GA : 163298 FS : 206731
## Median : 5.000 TX : 126100 BIA : 128871
## Mean : 4.475 NC : 105113 BLM : 112063
## 3rd Qu.: 7.000 FL : 87589 BC : 85833
## Max. :10.000 BC : 85833 USFS : 71387
## (Other):1318956 (Other): 224429Write out a .csv file
outfileuscan <- "uscan_1986-2013.csv"
write.table(uscan, outfileuscan, sep=",", row.names=FALSE)Save the .RData file.
# write out merged data
outfilename <- "uscan_1986-2013.RData"
save(uscan,file=outfilename)2 Basic characterization of the merged data
# Fire frequency
uscan_yearmon_count_all <- table(uscan$year, uscan$mon)
mosaicplot(uscan_yearmon_count_all, color=monthcolors, cex.axis=0.6, las=3,
main="US & Canada, All Fires, All Agencies -- Fire Frequency")
uscan_yearmon_count_light <- table(uscan$year[uscan$cause1 == 1], uscan$mon[uscan$cause1 == 1])
mosaicplot(uscan_yearmon_count_light, color=monthcolors, cex.axis=0.6, las=3,
main="US & Canada, Lightning Fires, All Agencies -- Fire Frequency")
uscan_yearmon_count_human <- table(uscan$year[uscan$cause1 == 2], uscan$mon[uscan$cause1 == 2])
mosaicplot(uscan_yearmon_count_human, color=monthcolors, cex.axis=0.6, las=3,
main="US & Canada, Human Fires, All Agencies -- Fire Frequency")
# Area burned
uscan_yearmon_sum_all <- aggregate(uscan$area_ha, by=list(uscan$year, uscan$mon), sum)
uscan_yearmon_sum_all_mat <- matrix(uscan_yearmon_sum_all$x, nrow=28, ncol=12)
dimnames(uscan_yearmon_sum_all_mat) <- dimnames(uscan_yearmon_count_all)
mosaicplot(uscan_yearmon_sum_all_mat, color=monthcolors, cex.axis=0.6, las=3,
main="US & Canada, All Fires, All Agencies -- Area Burned")
uscan_yearmon_sum_light <- aggregate(uscan$area_ha[uscan$cause1 == 1], by=list(uscan$year[uscan$cause1 == 1],
uscan$mon[uscan$cause1 == 1]), sum)
uscan_yearmon_sum_light_mat <- matrix(uscan_yearmon_sum_light$x, nrow=28, ncol=12)## Warning in matrix(uscan_yearmon_sum_light$x, nrow = 28, ncol = 12): data length [335] is not a sub-
## multiple or multiple of the number of rows [28]dimnames(uscan_yearmon_sum_light_mat) <- dimnames(uscan_yearmon_count_light)
mosaicplot(uscan_yearmon_sum_light_mat, color=monthcolors, cex.axis=0.6, las=3,
main="US & Canada, Lightning Fires, All Agencies -- Area Burned")
uscan_yearmon_sum_human <- aggregate(uscan$area_ha[uscan$cause1 == 2], by=list(uscan$year[uscan$cause1 == 2],
uscan$mon[uscan$cause1 == 2]), sum)
uscan_yearmon_sum_human_mat <- matrix(uscan_yearmon_sum_human$x, nrow=28, ncol=12)
dimnames(uscan_yearmon_sum_human_mat) <- dimnames(uscan_yearmon_count_human)
mosaicplot(uscan_yearmon_sum_human_mat, color=monthcolors, cex.axis=0.6, las=3,
main="US & Canada, Human Fires, All Agencies -- Area Burned")
2.1 Large fires only
cutsize <- 1.0
uscanlrg <- uscan[uscan$area_ha > cutsize,]# Fire frequency
uscanlrg_yearmon_count_all <- table(uscanlrg$year, uscanlrg$mon)
mosaicplot(uscanlrg_yearmon_count_all, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, All Fires >",as.character(cutsize),"ha, All Agencies -- Fire Frequency"))
uscanlrg_yearmon_count_light <- table(uscanlrg$year[uscanlrg$cause1 == 1], uscanlrg$mon[uscanlrg$cause1 == 1])
mosaicplot(uscanlrg_yearmon_count_light, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Lightning Fires >",as.character(cutsize),"ha, All Agencies -- Fire Frequency"))
uscanlrg_yearmon_count_human <- table(uscanlrg$year[uscanlrg$cause1 == 2], uscanlrg$mon[uscanlrg$cause1 == 2])
mosaicplot(uscanlrg_yearmon_count_human, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Human Fires >",as.character(cutsize),"ha, All Agencies -- Fire Frequency"))
# Area burned
uscanlrg_yearmon_sum_all <- aggregate(uscanlrg$area_ha, by=list(uscanlrg$year, uscanlrg$mon), sum)
uscanlrg_yearmon_sum_all_mat <- matrix(uscanlrg_yearmon_sum_all$x, nrow=28, ncol=12)
dimnames(uscanlrg_yearmon_sum_all_mat) <- dimnames(uscanlrg_yearmon_count_all)
mosaicplot(uscanlrg_yearmon_sum_all_mat, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, All Fires >",as.character(cutsize),"ha, All Agencies -- Area Burned"))
uscanlrg_yearmon_sum_light <- aggregate(uscanlrg$area_ha[uscanlrg$cause1 == 1], by=list(uscanlrg$year[uscanlrg$cause1 == 1],
uscanlrg$mon[uscanlrg$cause1 == 1]), sum)
uscanlrg_yearmon_sum_light_mat <- matrix(0,nrow=28, ncol=12)
for (i in seq(1:length(uscanlrg_yearmon_sum_light$x))) {
m <- uscanlrg_yearmon_sum_light$Group.2[i]
n <- uscanlrg_yearmon_sum_light$Group.1[i]-1986+1
uscanlrg_yearmon_sum_light_mat[n,m] <- uscanlrg_yearmon_sum_light$x[i]
}
dimnames(uscanlrg_yearmon_sum_light_mat) <- dimnames(uscanlrg_yearmon_count_light)
mosaicplot(uscanlrg_yearmon_sum_light_mat, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Lightning Fires >",as.character(cutsize),"ha, All Agencies -- Area Burned"))
uscanlrg_yearmon_sum_human <- aggregate(uscanlrg$area_ha[uscanlrg$cause1 == 2], by=list(uscanlrg$year[uscanlrg$cause1 == 2],
uscanlrg$mon[uscanlrg$cause1 == 2]), sum)
uscanlrg_yearmon_sum_human_mat <- matrix(uscanlrg_yearmon_sum_human$x, nrow=28, ncol=12)
dimnames(uscanlrg_yearmon_sum_human_mat) <- dimnames(uscanlrg_yearmon_count_human)
mosaicplot(uscanlrg_yearmon_sum_human_mat, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Human Fires >",as.character(cutsize),"ha, All Agencies -- Area Burned"))
2.2 Larger fires > 100 ha
cutsize <- 100.0
uscanlrg <- uscan[uscan$area_ha > cutsize,]# Fire frequency
uscanlrg_yearmon_count_all <- table(uscanlrg$year, uscanlrg$mon)
mosaicplot(uscanlrg_yearmon_count_all, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, All Fires >",as.character(cutsize),"ha, All Agencies -- Fire Frequency"))
uscanlrg_yearmon_count_light <- table(uscanlrg$year[uscanlrg$cause1 == 1], uscanlrg$mon[uscanlrg$cause1 == 1])
mosaicplot(uscanlrg_yearmon_count_light, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Lightning Fires >",as.character(cutsize),"ha, All Agencies -- Fire Frequency"))
uscanlrg_yearmon_count_human <- table(uscanlrg$year[uscanlrg$cause1 == 2], uscanlrg$mon[uscanlrg$cause1 == 2])
mosaicplot(uscanlrg_yearmon_count_human, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Human Fires >",as.character(cutsize),"ha, All Agencies -- Fire Frequency"))
# Area burned
uscanlrg_yearmon_sum_all <- aggregate(uscanlrg$area_ha, by=list(uscanlrg$year, uscanlrg$mon), sum)
uscanlrg_yearmon_sum_all_mat <- matrix(uscanlrg_yearmon_sum_all$x, nrow=28, ncol=12)
dimnames(uscanlrg_yearmon_sum_all_mat) <- dimnames(uscanlrg_yearmon_count_all)
mosaicplot(uscanlrg_yearmon_sum_all_mat, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, All Fires >",as.character(cutsize),"ha, All Agencies -- Area Burned"))
uscanlrg_yearmon_sum_light <- aggregate(uscanlrg$area_ha[uscanlrg$cause1 == 1], by=list(uscanlrg$year[uscanlrg$cause1 == 1],
uscanlrg$mon[uscanlrg$cause1 == 1]), sum)
uscanlrg_yearmon_sum_light_mat <- matrix(uscanlrg_yearmon_sum_light$x, nrow=28, ncol=12)## Warning in matrix(uscanlrg_yearmon_sum_light$x, nrow = 28, ncol = 12): data length [241] is not a
## sub-multiple or multiple of the number of rows [28]uscanlrg_yearmon_sum_light_mat <- matrix(0,nrow=28, ncol=12)
for (i in seq(1:length(uscanlrg_yearmon_sum_light$x))) {
m <- uscanlrg_yearmon_sum_light$Group.2[i]
n <- uscanlrg_yearmon_sum_light$Group.1[i]-1986+1
uscanlrg_yearmon_sum_light_mat[n,m] <- uscanlrg_yearmon_sum_light$x[i]
}
dimnames(uscanlrg_yearmon_sum_light_mat) <- dimnames(uscanlrg_yearmon_count_light)
mosaicplot(uscanlrg_yearmon_sum_light_mat, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Lightning Fires >",as.character(cutsize),"ha, All Agencies -- Area Burned"))
uscanlrg_yearmon_sum_human <- aggregate(uscanlrg$area_ha[uscanlrg$cause1 == 2], by=list(uscanlrg$year[uscanlrg$cause1 == 2],
uscanlrg$mon[uscanlrg$cause1 == 2]), sum)
uscanlrg_yearmon_sum_human_mat <- matrix(0,nrow=28, ncol=12)
for (i in seq(1:length(uscanlrg_yearmon_sum_human$x))) {
m <- uscanlrg_yearmon_sum_human$Group.2[i]
n <- uscanlrg_yearmon_sum_human$Group.1[i]-1986+1
uscanlrg_yearmon_sum_human_mat[n,m] <- uscanlrg_yearmon_sum_human$x[i]
}
dimnames(uscanlrg_yearmon_sum_human_mat) <- dimnames(uscanlrg_yearmon_count_human)
mosaicplot(uscanlrg_yearmon_sum_human_mat, color=monthcolors, cex.axis=0.6, las=3,
main=paste("US & Canada, Human Fires >",as.character(cutsize),"ha, All Agencies -- Area Burned"))