Package 'scfmutils'

Description

The original fire model is described by Cumming et al. (1998), and more accessibly in Armstrong and Cumming (2003). It has recently been implemented as a collection of 'SpaDES' modules by Cumming, McIntire, Eddy, and Chubaty, available from https://github.com/PredictiveEcology/scfm.

Author(s)

Maintainer: Alex M Chubaty [email protected] (ORCID)

Authors:

• Steve Cumming [email protected]

• Eliot J B McIntire [email protected] (ORCID)

• Ian M S Eddy [email protected] (ORCID)

Other contributors:

• His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources Canada [copyright holder]

See Also

Useful links:

• https://scfmutils.predictiveecology.org

• https://github.com/PredictiveEcology/scfmutils

• https://predictiveecology.github.io/scfmutils/

• Report bugs at https://github.com/PredictiveEcology/scfmutils/issues

Description

scfmRegime: calcZonalRegimePars

Usage

calcZonalRegimePars(
  polygonID,
  firePolys,
  firePoints,
  epochLength,
  maxSizeFactor,
  fireSizeColumnName,
  targetBurnRate = NULL,
  targetMaxFireSize = NULL
)

Arguments

Value

list containing the following elements and their values: ignitionRate (ignition rate), pEscape (escape probability), xBar (mean fire size), lxBar (mean log-fire-size), xMax (maximum observed fire size), emfs_ha (estimated maximum fire size in ha), empiricalBurnRate (empircal burn rate)

Description

Calibrate fire regime polygons ... (TODO)

Usage

calibrateFireRegimePolys(
  polygonType,
  targetN,
  fireRegimePolys,
  buffDist,
  pJmp,
  pMin,
  pMax,
  flammableMap = NULL,
  plotPath = NULL,
  outputPath = NULL,
  optimizer = "bfgs"
)

Arguments

Value

data.table with columns:

• PolyID: polygon ID;

• pSpread: spread probability;

• p0: TODO;

• naiveP0: TODO;

• pIgnition: ignition probability;

• maxBurnCells: maximum number of burned cells.

Description

Check for various issues with fireRegimePolys

Usage

checkForIssues(
  fireRegimePolys,
  studyArea,
  rasterToMatch,
  flammableMap,
  sliverThresh,
  cacheTag
)

Arguments

Value

a cleaned up fireRegimePolys object

Description

Create data.table to compare scfm predictions with historical observations

Usage

comparePredictions_summaryDT(
  fireRegimePoints = NULL,
  burnSummary = NULL,
  fireRegimePolys = NULL,
  times = NULL
)

comparePredictions_meanFireSize(dt)

comparePredictions_fireReturnInterval(dt, times)

comparePredictions_annualIgnitions(dt)

comparePredictions_annualEscapes(dt)

comparePredictions_fireDistribution(
  fireRegimePoints = NULL,
  burnSummary = NULL,
  size
)

Arguments

Value

comparePredictions_summaryDT returns a data.table object; other functions return ggplot objects.

Author(s)

Ian Eddy

Examples

## Not run: 
## assumes user has run scfm to produce the simList `mySimOut`
dt <- comparePredictions_summaryDT(fireRegimePoints = mySimOut$fireRegimePoints,
                                   burnSummary = mySimOut$burnSummary,
                                   fireRegimePolys = mySimOut$fireRegimePolys,
                                   times = times(mySimOut))

gg_mfs <- comparePredictions_meanFireSize(dt)
gg_fri <- comparePredictions_fireReturnInterval(dt)
gg_ign <- comparePredictions_annualIgnitions(dt)
gg_frp <- plot_fireRegimePolys(mySimOut$fireRegimePolys)

gridExtra::grid.arrange(fps,  gg_mfs,  gg_fri,  gg_ign, nrow = 2, ncol = 2)

## End(Not run)

Description

The threshold is applied to the area of the multipolygon object, not each individual polygon. Non-sliver polygons keep their original attributes. Intended to be used when it is important to retain the original extent of an area while removing sliver polygons.

Usage

deSliver(x, threshold)

Arguments

Value

an object of class sf with sliver polygons merged to their nearest valid neighbour.

Description

DESCRIPTION NEEDED

Usage

executeDesign(L, dT, maxCells)

Arguments

Value

TODO

Description

Create fire regime polygons for scfmRegime.

Usage

fireRegimePolyTypes()

prepInputsFireRegimePolys(
  url = NULL,
  destinationPath = tempdir(),
  studyArea = NULL,
  rasterToMatch = NULL,
  type = "ECOREGION"
)

Arguments

Examples

library(terra)
library(SpaDES.tools)

## random study area in central Alberta
studyAreaAB <- vect(cbind(-115, 55), crs = "epsg:4326") |>
  project(paste("+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95",
                "+x_0=0 +y_0=0 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0")) |>
  randomStudyArea(seed = 60, size = 1e10)

studyAreaBC <- vect(cbind(-122.14, 52.14), crs = "epsg:4326") |>
  project(paste("+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95",
                "+x_0=0 +y_0=0 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0")) |>
  randomStudyArea(seed = 60, size = 1e10)


frpEcoregion <- prepInputsFireRegimePolys(studyArea = studyAreaAB, type = "ECOREGION")
plot(frpEcoregion)



frpBECNDT <- prepInputsFireRegimePolys(studyArea = studyAreaBC, type = "BECNDT")
plot(frpBECNDT)


frpFRT <- prepInputsFireRegimePolys(studyArea = studyAreaAB, type = "FRT")
plot(frpFRT)

frpFRU <- prepInputsFireRegimePolys(studyArea = studyAreaAB, type = "FRU")
plot(frpFRU)

Description

scfmLandCoverInit: genFireMapAttr

Usage

genFireMapAttr(flammableMap, fireRegimePolys, neighbours)

Arguments

Value

TODO

Description

Buffers polygon, generates index raster

Usage

genSimLand(coreLand, buffDist, flammableMap = NULL)

Arguments

Value

list containing fireRegimePoly, landscapeIndex, flammableMap objects.

Description

Get fire points data from the Canadian National Fire Database

Usage

getFirePoints_NFDB_scfm(
  url = NULL,
  studyArea = NULL,
  rasterToMatch = NULL,
  redownloadIn = 2,
  NFDB_pointPath = NULL
)

Arguments

Description

1 - (1-p0)**N = pEscape
1 - pEscape = (1-p0)**N
(1 - pEscape)**1/N = 1 - p0
p0 = 1 - (1 - pEscape)**1/N
```

Usage

hatP0(pEscape, n = 8)

escapeProbDelta(p0, w, hatPE)

Arguments

Value

TODO

Description

This is a wrapper around makeDesign and executeDesign.

Usage

makeAndExecuteDesign(...)

Arguments

Value

output of executeDesign (TODO)

Description

scfmDriver: makeDesign

Usage

makeDesign(indices, targetN, pEscape = 0.1, pmin, pmax, q = 1)

Arguments

Value

data.frame with columns igLoc, p0, and p.

Note

This version of makeDesign is the simplest possible.

Description

Plot age map

Usage

plot_ageMap(x, title, maxAge)

Arguments

Value

ggplot object

Description

Plot burn maps

Usage

plot_burnMap(x, title)

Arguments

Value

ggplot object

Description

Plot fire regime polygons

Usage

plot_fireRegimePolys(fireRegimePolys)

Arguments

Value

a ggplot object

Description

Plot fire regime raster

Usage

plot_fireRegimeRas(x, title)

Arguments

Value

ggplot object

Description

Plot flammable map

Usage

plot_flammableMap(x, title)

Arguments

Value

ggplot object

Description

$Z ~ TE(\theta, T)$: pdf is $\frac{\theta \exp(-z \theta)}{1 - \exp(-T\theta)}$

Usage

pTE(x, theta, T)

dTE(x, theta, T)

qTE(p, theta, T)

rTE(n, theta, T)

qqTE(
  x,
  theta = stop("missing theta"),
  T = stop("missing T"),
  plot.it = TRUE,
  xlab = deparse(substitute(x)),
  ylab = deparse(substitute(y)),
  ...
)

ETE(theta, T, a = 0)

ETEx(theta, T, a = 0, shift = 200)

ExpBar(Z)

HannonDayiha(Z, Tspec = 0)

Arguments

Details

where T is the truncation point or upper bound and $\theta$ is the shape parameter in this application, x are fire sizes ⁠>= shift⁠, which is a lower bound and z = log(x / shift) are the scaled log transformed sizes which seem to fit a truncated exponential distribution fairly well.

Originally written by Steve in 1999 in support of Cumming CJFR 2001. Has been in use by BEACONs and was acquired from Pierre Vernier in May 17 2014.

• pTE() is the distribution function;

• dTE() is the density function;

• qTE() is the quantile function;

• rTE() is the random generation function. In fire size applications exp(rTE(n, theta, T)) * shift will generate n random fire sizes;

• qqTE() produces a quantile-quantile plot of vector x against a TE(theta, T);

• ETE() is TODO;

• ETEx() is TODO;

• ExpBar() is TODO;

• HannonDayiha() implements the estimator of Hannon and Dayiha (1999), ported from 1999 C language implementation by SGC June 2004.

References

Patrick M. Hannona & Ram C. Dahiyaa (1999) Estimation of parameters for the truncated exponential distribution. Communications in Statistics - Theory and Methods 28(11): 2591-2612. doi:10.1080/03610929908832440.

Description

Ratio partition

Usage

ratioPartition(targetBurnRate, empiricalBurnRate, pEscape, xBar, rate)

ratioPartition2(targetBurnRate, empiricalBurnRate, pEscape, xBar, rate)

Arguments

Value

a list containing the following elements: rate (ignition rate), pEscape (escape probability), xBar (mean fire size).

Description

unirootFunction

Usage

unirootFunction(x, cM, xBar)

Arguments

Value

TODO