title	fireSense_dataPrepFit Manual
subtitle	v.1.3.0
date	Last updated: 2026-10-08
output	bookdown::html_document2 toc toc_float theme number_sections df_print keep_md true true sandstone false paged true
editor_options	chunk_output_type console
bibliography	citations/references_fireSense_dataPrepFit.bib
link-citations	true
always_allow_html	true

fireSense_dataPrepFit Module

(ref:fireSense-dataPrepFit) fireSense_dataPrepFit

Authors:

Ian Eddy ian.eddy@nrcan-rncan.gc.ca [aut, cre], Eliot McIntire eliot.mcintire@nrcan-rncan.gc.ca [aut], Alex M Chubaty achubaty@for-cast.ca [ctb]

Module Overview

Prepares the data needed to fit fireSense_ignitionFit (ignition and escape) and fireSense_spreadFit.

Module summary

The module combines historical fire records, vegetation, land cover and climate into the covariate tables used to fit the three fireSense processes [@Marchal:2017a; @Marchal:2017b; @Marchal:2019]: ignition, escape (an ignition that grows beyond one pixel) and spread.

Vegetation, land cover and stand age are snapshots, one per year in P(sim)$dataYears (default 2000, 2010, 2020). Each year in P(sim)$fireYears uses the snapshot at or before it, so no fire year may precede the first data year, and every data year needs at least one fire year. Climate is annual and is matched to the year of each fire. Ignition and escape share climate variables (sim$climateVariablesForFire$ignition); spread can use others ($spread).

By default the module builds its own inputs:

• land cover (rstLCCs) with fireSenseUtils::makeFireSenseLCC() and stand age with LandR::prepInputsStandAgeMap(), per data year;
• cohortDatas and pixelGroupMaps, by running Biomass_borealDataPrep (and Biomass_speciesData, if it is in the project) in a nested simInitAndSpades() per data year. This is cached. Missing modules are downloaded to this module's submodules folder;
• fire polygons from the latest NBAC release, and ignition points (lightning- and natural-caused only) from the current NFDB release.

historicalClimateRasters has no default and must be supplied, e.g., by canClimateData. It must cover every fire year; the module stops otherwise.

Previous SpreadFit results

At init, the module looks in a Google Drive ledger (P(sim)$spreadFitGoogleDriveFolder, P(sim)$spreadFitFilename) for SpreadFit results that overlap sim$studyArea. If there are any, sppEquiv, the fuel classes, the non-forest groups and the spread climate variables are taken from that fit, and fuel classes are not estimated. sim$climateVariables must then be supplied.

Fuel classes

If P(sim)$estimateFuelClasses is TRUE, and the user supplied none of nonForestedLCCGroups, fuelClassTable or a modified FuelClass column in sppEquiv, fuel classes are estimated with fireSenseUtils::assessFuelClasses().

Non-forest land cover classes are grouped by their historical propensity to burn, estimated with a GLM, into two groups.

For forest, each species starts as its own fuel class with an a priori class, by default an interpretation of the FBP fuel types (LandR::sppEquivalencies_CA$FuelClass). A GLM relates the biomass of each species, in pixels where it is present, to whether the pixel burned. Species are then merged until P(sim)$targetFuelClasses (default 5) remain:

1. Abundance is the proportion of forested pixels where the species is more than 10% of the biomass.
2. Rare species (abundance < 5%) are merged with another species of the same a priori class, least abundant first. This can leave fewer classes than the target.
3. If there are still too many classes, the next least abundant species are merged, but only with species of the same a priori class and the same coefficient sign (or a non-significant one).

::: {.example #of semi-automated fuel classes} 7 species were initially present on the landscape; 2 must be combined to achieve the target 5 in this case, Betu_pap and Popu_tre were combined due to their low abundance (above10PctRelB) Pice_gla and Pice_eng were combined due as Abie_las was the most abundant. Pice_mar and Pinu_con were not combined as there were no other species with similar FuelClass values

species	coef	sign	FuelClass	Abundance	newFuelClass
Pice_mar	-0.01320	negative	BlkSprc	0.066	Pice_mar
Pinu_con	0.00154	positive	LdJkPine	0.625	Pinu_con
Betu_pap	-0.00170	negative	PopBrch	0.051	Bt_pa.Pp_tr
Pice_eng	-0.01910	negative	SprcFrLrch	0.095	Pc_en.Pc_gl
Popu_tre	-0.02100	negative	PopBrch	0.223	Bt_pa.Pp_tr
Pice_gla	-0.00920	negative	SprcFrLrch	0.352	Pc_en.Pc_gl
Abie_las	-0.00630	negative	SprcFrLrch	0.560	Abie_las

:::

youngAge, missingLCCgroup and treed wetland

Pixels disturbed within P(sim)$cutoffForYoungAge years (default 15) are youngAge, a fuel class of its own. Time since disturbance comes from the stand age maps and the fire polygons (firePolysForAge), per data year. Non-forest pixels can also be youngAge, unless P(sim)$nonForestCanBeYoungAge is FALSE.

sim$nonForestedLCCGroups takes precedence over P(sim)$forestedLCC: a land cover class listed in a non-forest group is a categorical fuel even if it is also in forestedLCC. This lets treed wetland, for example, be simulated as forest by LandR but be a land cover fuel in fireSense. A flammable class in neither gets no fuel covariate.

Pixels with forested land cover but no cohorts (usually because there was no species data) have no biomass, so they are assigned to one of the non-forest groups, sim$missingLCCgroup. It is estimated along with the fuel classes; otherwise it defaults to the first group.

Usage

The module is normally run with canClimateData (for historicalClimateRasters and climateVariables) ahead of the three fit modules. fireSense_spreadFit preparation needs the ignition preparation, so keep fireSense_ignitionFit in P(sim)$whichModulesToPrepare. Preparing fireSense_ignitionFit also prepares the escape data (prepEscapeFitData); the module fireSense_EscapeFit no longer exists and is rejected.

out <- SpaDES.project::setupProject(
  paths = list(projectPath = "~/fireSenseFit"),
  modules = c("PredictiveEcology/canClimateData@development", # needs its own parameters
              "PredictiveEcology/fireSense_dataPrepFit@development"),
  times = list(start = 2020, end = 2020),
  studyArea = mySA, # buffered to limit edge effects
  params = list(fireSense_dataPrepFit = list(
    .useCache = c(".inputObjects", "dataPrepBuild", "prepIgnitionFitData",
                  "prepEscapeFitData", "prepSpreadFitData")))
)
sim <- do.call(SpaDES.core::simInitAndSpades, out)

Module inputs and parameters

Table @ref(tab:moduleInputs-fireSense-dataPrepFit) shows the full list of module inputs.

(\#tab:moduleInputs-fireSense-dataPrepFit)(\#tab:moduleInputs-fireSense-dataPrepFit)List of (ref:fireSense_dataPrepFit) input objects and their description.

objectName	objectClass	desc	sourceURL
climateVariables	list	Climate variable definitions for `climateData::prepClimateLayers` (canClimateData). Unless supplied, `.inputObjects` builds them from `climateVariablesForFire`. Declared as an input because `.inputObjects` sets it: a cached `.inputObjects` restores only declared inputs, so without this a cache hit returned no `climateVariables` and canClimateData failed.	NA
climateVariablesForFire	list	List with elements `ignition` and `spread`, each a character vector of climate variable names, with or without underscores (e.g., `CMD_sm` or `CMDsm`). IgnitionFit uses all of `ignition`; SpreadFit uses `spread`. Default: `ignition = c('CMD', 'cumMDC', 'CMD_sm', 'CMD_sp')`, `spread = 'auto'`: the `ignition` variable that best separates the study area's worst fire years (see `spreadClimateSelection`). Unless supplied, `climateVariables` is built from these.	NA
cohortDatas	list	List of `cohortData` data.tables, one per `dataYears`, named `year<year>`. If not supplied, built by running Biomass_borealDataPrep for each data year.	NA
spreadFirePoints	list	List of spatial points, one per fire year, named `year<year>`; each point is the ignition location of one fire in `firePolys`. The default is the polygon centroids.	NA
spreadFitAdditionalColNames	character	Names of the ledger (`spreadFitPreRun`) columns to read. The default is `fireSenseUtils::spreadFitAdditionalColNamesTxt`.	NA
firePolys	list	List of fire polygons, one per year in `fireYears`, named `year<year>`. The default is the latest NBAC release.	NA
firePolysForAge	list	List of annual fire polygons used for time since disturbance; as `firePolys`, but starting `cutoffForYoungAge` years before the first of `fireYears`.	NA
historicalFireRaster	SpatRaster	Optional raster of fire year, 1985-2020. If supplied it replaces `firePolysForAge` for time since disturbance. Only downloaded when `useRasterizedFireForSpread = TRUE`.	https://opendata.nfis.org/downloads/forest_change/CA_Forest_Fire_1985-2020.zip
historicalClimateRasters	list	List of SpatRasters of historical climate, named by climate variable, with layers named `year<year>`. Must be supplied, and must cover `fireYears`.	NA
ignitionFirePoints	SpatVector	Points of annual ignitions, of every fire size, with columns `YEAR` and `SIZE_HA`. The default is the lightning- and natural-caused fires of the current NFDB release.	NA
missingLCCgroup	character	The `nonForestedLCCGroups` name given to forested pixels that are absent from `cohortData`. The default is the first name; it is replaced if fuel classes are estimated.	NA
nonForestedLCCGroups	list	Named list of non-forest land cover classes, e.g. `list(wetland = c(19, 23, 32))`. Each group becomes a fuel covariate. The default is one group, `nf`, of every class that is neither forested nor non-flammable; it is replaced if fuel classes are estimated.	NA
pixelGroupMaps	list	List of `pixelGroupMap` SpatRasters matching `cohortDatas`, named `year<year>`.	NA
propFlammables	list	List of SpatRasters of the proportion of flammable land cover in a pixel, one per `dataYears`. Built with `rstLCCs` when that is not supplied.	NA
rasterToMatch	SpatRaster	Template raster for `studyArea`. The default is 240 m, from SCANFI land cover.	NA
rasterToMatchLarge	SpatRaster	Optional larger template. If supplied it defines `studyArea_biomassParam`; if not, `.inputObjects` sets it to `rasterToMatch` for Biomass_speciesData. Declared as an input because `.inputObjects` sets it (a cached `.inputObjects` restores only declared inputs).	NA
rasterToMatch_biomassParam	SpatRaster	Template raster for `studyArea_biomassParam`, passed to Biomass_borealDataPrep. Expected to cover at least `rasterToMatch` (formerly `rasterToMatchLarge`).	NA
rstLCCs	list	List of land cover SpatRasters, one per `dataYears`, named `year<year>`, on `rasterToMatch_biomassParam`. The default is from `fireSenseUtils::makeFireSenseLCC`.	NA
.ELFind	character	The ELF this run is for (`fireSenseUtils::polygonIDTxt` in the SpreadFit ledger), set by `fireSense_ELFs`; its row's species colours win when ledger rows disagree. Optional.	NA
sppEquiv	data.table	Table of LandR species equivalencies. The default is from `LandR::speciesInStudyArea`.	NA
standAgeMaps	list	List of stand age SpatRasters, one per `dataYears`, named `year<year>`; used to create `cohortDatas` and time since disturbance.	NA
spreadFirePolys	list	Not needed from the user: `firePolys` in the CRS of `rasterToMatch`, declared as an input because a later event modifies it.	NA
spreadFitPreRun	data.frame	Ledger rows of previous SpreadFit results, as the output of that name; `Init()` reads them (supplied by `fireSense_ELFs`). Declared as an input so the rows are in the cache keys of this module's cached events: otherwise a cache entry saved before an ELF was refitted restores its old row over the one `Init()` just read.	NA
studyArea	SpatVector	Study area for all data. Should be buffered to limit edge effects on fire spread.	NA
studyArea_biomassParam	SpatVector	study area passed to Biomass_borealDataPrep for vegetation calibration	NA

Parameters are in Table @ref(tab:moduleParams-fireSense-dataPrepFit).

(\#tab:moduleParams-fireSense-dataPrepFit)(\#tab:moduleParams-fireSense-dataPrepFit)List of (ref:fireSense-dataPrepFit) parameters and their description.

paramName	paramClass	default	min	max	paramDesc
areaMultiplier	numeric,....	::, fire....	NA	NA	Size of the unburned buffer sampled around each fire: a scalar (buffer area is `areaMultiplier fireSize`) or a quoted function of `fireSize`. See `?fireSenseUtils::bufferToArea`.
bufferForFireRaster	numeric	1000	0	NA	Buffer distance within which separate patches of burned pixels count as one fire. Only used when `useRasterizedFireForSpread = TRUE`.
cutoffForYoungAge	numeric	15	NA	NA	Age at and below which pixels are considered 'young' (`young <- age <= cutoffForYoungAge`)
dataYears	integer	1985, 19....	NA	NA	Two or more increasing years for which vegetation, land cover and stand age are built (`cohortDatas`, `rstLCCs`, `standAgeMaps`, ...). Each fire year uses the data year at or before it, so no `fireYears` may precede the first, and every data year needs at least one fire year before the next data year.
estimateFuelClasses	logical	TRUE	NA	NA	Estimate fuel classes with `fireSenseUtils::assessFuelClasses`? Skipped if the user supplies `nonForestedLCCGroups`, `fuelClassTable` or a `FuelClass` column that differs from LandR's, or if a previous SpreadFit exists for the study area.
fireYears	integer	1985, 19....	NA	NA	Years of fire records to use for fitting. None may precede the first of `dataYears`, and `historicalClimateRasters` must cover all of them. The default runs from 1985, the first SCANFI V2 year, to the latest year with historical climate for every tile (`climateData::latestHistoricalYear()`); climate is the last of the inputs to reach a year.
flammabilityThreshold	numeric	0.1	0	1	Minimum proportion of flammable fine-resolution land cover for a `rasterToMatch` pixel to be flammable. Only used when `rstLCCs` is built here.
forestedLCC	numeric	81, 210,....	NA	NA	Forested land cover classes - these differ from non-forest because the biomass and composition of fuels are taken into account by fireSense, while non-forest classes are treated categorically
igAggFactor	numeric	4	1	NA	Aggregation factor (number of `rasterToMatch` cells per side) for the ignition and escape covariates.
escapeSizeHa	numeric	50	0	NA	Size (ha) a fire must reach to count as escaped: the escape model's response, and the smallest fire the spread model is fitted to. Smaller fires' sizes become `nonEscapedFireSizesHa`.
fuelClassCol	character	FuelClass	NA	NA	the column in `sppEquiv` that defines unique fuel classes. A column named `FuelClass` exists in the `LandR::sppEquivalencies_CA` and will be used by default. To change the `FuelClass` classifications, add a column to that table, or to `sim$sppEquiv` and then modify this `fuelClassCol` parameter
fuelCovariates	character	domSecWe....	NA	NA	How the spread-fit fuel covariates are represented. `"domSecWetland"` (default): `dom_agb_<class>` and `sec_agb_<class>` (the two fuel classes with the most total treed AGB over the fit study area) and `treedWetland_agb` (all tree AGB on treed-wetland pixels, removed from dom/sec there); other classes are not covariates; see `fireSenseUtils::fireSenseCovariatesCreate()`. `"species"`: the previous one column per fuel class. `fireSense_dataPrepPredict` follows whichever a fit used; this is not a parameter there.
minBufferSize	numeric	5000	NA	NA	Minimum number of cells in each fire's burned-plus-buffer sample, applied after `areaMultiplier`.
minCovariateProp	numeric	0.05	0	1	A land-cover class covering less than this proportion of the ELF's flammable pixels (most recent data year) is too rare to estimate a spread coefficient for. A non-forest class joins the non-forest group nearest its burn rate instead of being clustered on its own (`fireSenseUtils::assessFuelClasses()`); with less treed wetland than this there is no `treedWetland_agb` and its tree AGB stays in `dom_agb_ `/`sec_agb_ ` (`fireSenseUtils::fireSenseCovariatesCreate()`). `0` keeps every class.
nonflammableLCC	numeric	0, 20, 3....	NA	NA	Non-flammable classes in `rstLCCs`; the default, `fireSenseUtils::fireSenseNonflammableLCC`, is no data, water, rock, snow/ice and barren land.
nonForestCanBeYoungAge	logical	TRUE	NA	NA	if TRUE, burned non-forest will be treated as `youngAge`. Recommended to be TRUE as burned forest is often classified as non-forest. `youngAge` is resolved for each fire year from the data year's time since disturbance, which covers forest and non-forest alike, so `FALSE` is not supported and stops the spread and ignition preparation.
scanfiVersion	character	V3	NA	NA	SCANFI land-cover version for non-forest land cover, `"V2"` or `"V3"`. Passed to `fireSenseUtils::makeFireSenseLCC()`.
sppEquivCol	character	LandR	NA	NA	column name in `sppEquiv` object that defines unique species in `cohortData`
heldOutFold	integer	NA	NA	NA	NA (default): unchanged. `1` or `2`: a cross-validation fold is being fitted (the same parameter as in `fireSense_spreadFit`), so the SpreadFit ledger is not relevant and `Init()` does not read it: `sim$spreadFitPreRun` stays NULL and this module derives the species, fuel and climate objects itself, as for an unfitted study area. Set it for every fireSense module at once with `.globals = list(heldOutFold = 1L)`; `Init()` stops if `fireSense_spreadFit` has a different value. Any other value is an error.
spreadFitGoogleDriveFolder	character	https://....	NA	NA	URL of the Google Drive folder holding the ledger of previous SpreadFit results (`spreadFitFilename`), read with `reproducible::CacheGeo`.
spreadFitFilename	character	latest	NA	NA	Name of the ledger file in `spreadFitGoogleDriveFolder`: study area polygons with their fitted SpreadFit parameters. `"latest"` (the default) takes each polygon's fit from the most recent ledger file that has it (`fireSenseUtils::latestSpreadFits()`).
spreadIntercept	logical	FALSE	NA	NA	If `TRUE`, the spread formula has an intercept (`~ 1 + ...`) and `fireSense_spreadFit` fits it, with the covariates centred, so the coefficients describe variation and the intercept the level. Covariates are rescaled to 0-1 and so are all >= 0: without an intercept the level of the linear predictor is set by the coefficients alone, and a climate coefficient trades off against the fuel and non-forest ones (ELF 13.1). `FALSE` (default) keeps `~ 0 + ...`. Ignored if `sim$fireSense_spreadFormula` is supplied. Needs a `fireSense_spreadFit` and a `fireSense_spreadPredict` that know the intercept.
targetFuelClasses	numeric	5	1	7	the target number of unique fuel classes when using semi-automated approach
useRasterizedFireForSpread	logical	FALSE	NA	NA	Use `historicalFireRaster` in place of fire polygons for spread? Not currently supported: `TRUE` stops with an error when preparing SpreadFit.
whichModulesToPrepare	character	fireSens....	NA	NA	Which fireSense fit modules to prep? defaults to both. Preparing `fireSense_ignitionFit` prepares its ignition and escape data.
.studyAreaName	character		NA	NA	`studyArea` name used in file names and cache tags; `NULL` derives it from `sim$studyArea`.
.useCache	logical	FALSE	NA	NA	Should this entire module be run with caching activated? This is intended for data-type modules, where stochasticity and time are not relevant
.useCacheArgs	list	list(.ca....	NA	NA	Extra `reproducible::Cache()` arguments, by event. A cached event's digest covers this module's code but not the package functions it calls, so `dataPrepBuild` and `prepSpreadFitData` pass those in `.cacheExtra`: a changed function then re-runs the event.

Events

All events run once, at start(sim).

init

Checks Google Drive for a previous SpreadFit (see above). It cannot be cached, because that would freeze the answer.

dataPrepBuild

Runs straight after init, before other modules' init. Puts rstLCCs on rasterToMatch, and builds, per data year, flammableRTMs, landcoverDTs and nonForest_timeSinceDisturbances. Fuel classes are estimated here. Can be cached: add "dataPrepBuild" to .useCache.

prepIgnitionFitData

Fuel, climate and lightning rasters are aggregated by P(sim)$igAggFactor, and ignitions are counted per coarse pixel and year. sim$fireSense_ignitionCovariates has one row per coarse pixel and year. Fitted probabilities only apply at that resolution, so the template sim$ignitionFitRTM is also output, with attributes nonNAs (the number of rows) and meanForestB. No ignition formula is built: fireSense_ignitionFit fits with xgboost, which does not use one.

prepEscapeFitData

Adds an escapes column to the ignition covariates: the ignitions that grew beyond one rasterToMatch pixel (not one coarse pixel). Builds sim$fireSense_escapeFormula if it was not supplied. Needs prepIgnitionFitData.

prepSpreadFitData

Spread uses fires of every cause, where ignition uses lightning- and natural-caused ones only, and only fires larger than one pixel. Each fire needs an ignition point in a flammable pixel inside its polygon (sim$spreadFirePoints; default the polygon centroid); fireSenseUtils::harmonizeFireData() enforces this. Each fire polygon is buffered, with the buffer size set by P(sim)$areaMultiplier and P(sim)$minBufferSize, and only burned and buffer pixels are kept (sim$fireBufferedListDT). The module stops if buffer pixels are fewer than five times the burned pixels.

To keep the objects small for the optimizer, the covariates are split in two: sim$fireSense_annualSpreadFitCovariates, one table of climate per fire year, and sim$fireSense_nonAnnualSpreadFitCovariates, one table of fuels per data year. Fuel columns that are all zero are dropped. Builds sim$fireSense_spreadFormula if it was not supplied. P(sim)$useRasterizedFireForSpread = TRUE is not currently supported.

plotAndMessage, cleanUp

plotAndMessage is a placeholder; cleanUp frees memory.

Module outputs

Description of the module outputs (Table @ref(tab:moduleOutputs-fireSense-dataPrepFit)).

(\#tab:moduleOutputs-fireSense-dataPrepFit)(\#tab:moduleOutputs-fireSense-dataPrepFit)List of (ref:fireSense-dataPrepFit) outputs and their description.

objectName	objectClass	desc
climateVariablesForFire	list	As the input. If a previous SpreadFit exists, `spread` becomes the climate variables of that fit, and they are added to `ignition`.
spreadFitPreRun	data.frame	Ledger rows of previous SpreadFit results that overlap `studyArea`, from `CacheGeo`: a geometry column (convert with `sf::st_as_sf`), plus `polygonID` and the columns in `spreadFitAdditionalColNames`. `NULL` if there is no previous fit.
studyAreaWithSpreadParams	sf	Same as `spreadFitPreRun`; not created if there is no previous fit.
sppColorVect	character	Named vector of hex colours, one per species. Only created if a previous SpreadFit exists, from the `sppEquiv` stored with it.
sppNameVector	character	Sorted species names (`sppEquivCol`) from the `sppEquiv` stored with a previous SpreadFit; only created if one exists.
spreadClimateSelection	data.table	With `climateVariablesForFire$spread = 'auto'`: each candidate's AUC for separating the worst quarter of fire years (by area burned), its Spearman correlation, and which was chosen.
climateVariables	list	Climate variable definitions, as used by `climateData::prepClimateLayers` (canClimateData). Unless supplied, built from `climateVariablesForFire` for `fireYears` (and projected years unless canClimateData's `climateGCM` is 'NRV'). If a previous SpreadFit exists, the variables of that fit are added.
fireBufferedListDT	list	list of data.tables with fire id, `pixelID`, and buffer status
fuelClassTable	data.table	Fuel class assigned to each tree species; only created if fuel classes are estimated.
spreadFirePolys	list	List of annual fire polygons used for SpreadFit: larger than one pixel and matched to `spreadFirePoints`.
fireSense_annualSpreadFitCovariates	list	List of data.tables, one per fire year, of `pixelID` and the spread climate covariates in the fire buffers.
fireSense_escapeCovariates	data.table	ignition covariates with added column of escapes
nonEscapedFireSizesHa	numeric	Sizes (ha) of this study area's natural-cause fires (`ignitionFirePoints`) below `escapeSizeHa`, for giving a forecast's non-escaped ignitions a size.
fireSense_escapeFormula	character	formula for escape, using fuel classes and landcover, as character
fireSense_ignitionCovariates	data.table	table of aggregated ignition covariates with annual ignitions
fireSense_nonAnnualSpreadFitCovariates	list	List of data.tables, one per `dataYears`, of `pixelID` and the fuel covariates in the fire buffers.
fireSense_spreadFormula	character	formula for spread, using climate and vegetation covariates, as character
fuelClassRoles	list	Only when `fuelCovariates = "domSecWetland"`: `list(domClass =, secClass =)`, the fuel classes chosen once for this ELF by `fireSenseUtils::chooseDomSecFuelClasses()`. Both `NA` with `fuelCovariates = "species"` or when the ELF has no tree fuel class.
ignitionFirePoints	SpatVector	The input, in the CRS of `rasterToMatch` and clipped to `studyArea`.
ignitionFitRTM	SpatRaster	Template raster with the resolution and extent of `fireSense_ignitionCovariates`. Attributes: `nonNAs`, the number of rows in that table, and `meanForestB`, the mean forest biomass per pixel.
landcoverDTs	list	List of data.tables, one per `dataYears`, of `pixelID` and a 0/1 column per non-forest group, for flammable pixels.
lightningMaps	SpatRaster	A 4-layer SpatRaster of lightning: lightningDays, lightningDensity, positiveCG, positiveCGdensity
missingLCCgroup	character	As the input, or the estimated group if fuel classes are estimated.
nonForestedLCCGroups	list	As the input, or the estimated groups if fuel classes are estimated.
nonForest_timeSinceDisturbances	list	List of SpatRasters, one per `dataYears`, of years since disturbance in flammable pixels, forested or not.
rstLCCs	list	The input, on `rasterToMatch`.
flammableRTMs	list	List of binary SpatRasters of flammable land cover on `rasterToMatch`, one per `dataYears`.
sppEquiv	data.table	sppEquiv table potentially modified with new or overwritten fuel class
spreadFirePoints	list	List of ignition points, one per fire year, for fires larger than one pixel, harmonized with `spreadFirePolys`.
propFlammable	SpatRaster	Last element of `propFlammables`.
standAgeMap	SpatRaster	Last element of `standAgeMaps`.
rstLCC_RTM	SpatRaster	Last element of the output `rstLCCs`, i.e., on `rasterToMatch`.
rstLCC	SpatRaster	Last element of the input `rstLCCs`, i.e., on `rasterToMatch_biomassParam`.
flammableRTM	SpatRaster	Last element of `flammableRTMs`.
landcoverDT	data.table	Last element of `landcoverDTs`.
nonForest_timeSinceDisturbance	SpatRaster	Last element of `nonForest_timeSinceDisturbances`.

Links to other modules

This module links to fireSense_ignitionFit and fireSense_spreadFit

Getting help

Contact the authors for help.

https://github.com/PredictiveEcology/fireSense_dataPrepFit/issues

References