Description Usage Arguments Value Author(s) References Examples
Prediction of crown fire probability, crown fire rate of spread and separation distance (Alexander and Cruz 2006). Separation distance is distance ahead of main fire front required for a spot fire to form, separate of a main fire.
1 | cfis(fsg, u10, effm, sfc, cbd, id)
|
fsg |
a numeric vector of fuel stratum gaps (m) |
u10 |
a numeric vector of 10-m open wind speeds (km/hr) |
effm |
a numeric vector of effective fine fuel moistures (%) |
sfc |
a numeric vector of surface fuel consumed (Mg/ha) |
cbd |
a numeric vector of canopy bulk densities (kg/m3) |
id |
a numeric vector of spot ignition delays, the time during which a given firebrand generates, is transported aloft, and ignites a receptive fuelbed (min) |
a data frame with type of fire, probability of crown fire occurrences (%), crown fire rate of spread (m/min), and critical spotting distance (m)
Justin P Ziegler, justin.ziegler@colostate.edu
Alexander M.E., Cruz M.G. 2006. Evaluating a model for predicting active crown fire rate of spread using wildfire observations. Canadian Journal of Forest Research. 36:2015-3028.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | data("coForest")
# show the data format:
head(coForest)
# Predict crown fire, using coForest
# measurements and assumed weather
# parameters
df.cfis = cfis(fsg = coForest$cbh_m, u10 = 20,
effm = 6, sfc = coForest$sfl_kgm2*10, cbd = coForest$cbd_kgm3,
id = 1)
print(df.cfis)
# Examine differences between treatment
# statuses
aggregate(x = df.cfis$cROS, by = list(treatmentStatus = coForest$status),
FUN = mean)
# Now, examine the sensitivity of fire
# type designations to wind speed by
# treatment status
coForest = coForest[rep(seq_len(nrow(coForest)),
11), ]
coForest$u10 = sort(rep(10:20, 14))
coForest$type = cfis(coForest$cbh_m, coForest$u10,
6, coForest$sfl_kgm2*10, coForest$cbd_kgm3,
1)$type
table(u10 = coForest$u10, coForest$type,
coForest$status)
|
site status trees_perha basalArea_m2ha qmd_cm height_m sfl_kgm2 cbd_kgm3
1 Heil pre 418 19.1 24.1 9.8 1.04 0.14
2 Heil post 295 14.5 25.0 10.1 0.76 0.10
3 Unc pre 504 30.0 27.5 22.1 1.20 0.15
4 Unc post 314 17.6 16.7 25.5 1.06 0.08
5 Pike pre 934 24.8 18.4 15.8 1.33 0.15
6 Pike post 352 9.5 18.5 16.6 1.33 0.06
cbh_m cfl_kgm2
1 3.63 0.837
2 3.69 0.628
3 4.35 2.653
4 4.14 1.674
5 2.90 2.096
6 3.60 0.830
type pCrown cROS sepDist
1 active 99.30 40.54 381.88
2 active 89.63 38.03 358.23
3 active 98.84 41.08 386.92
4 passive 99.00 13.79 129.91
5 active 99.58 41.08 386.92
6 passive 99.32 17.31 163.03
7 passive 99.66 13.79 129.91
8 passive 91.40 19.13 180.17
9 active 78.55 39.97 376.54
10 active 50.50 38.03 358.23
11 active 90.82 40.54 381.88
12 passive 90.21 17.31 163.03
13 active 88.67 37.28 351.13
14 passive 81.92 22.36 210.59
treatmentStatus x
1 post 23.70857
2 pre 36.32571
, , = post
u10 active passive surface
10 0 2 5
11 0 2 5
12 0 2 5
13 0 2 5
14 0 5 2
15 0 5 2
16 1 5 1
17 1 5 1
18 1 5 1
19 1 5 1
20 2 5 0
, , = pre
u10 active passive surface
10 3 1 3
11 3 1 3
12 3 1 3
13 3 1 3
14 4 1 2
15 4 2 1
16 4 2 1
17 5 2 0
18 6 1 0
19 6 1 0
20 6 1 0
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