Function reference • LandR

All functions
`BioSIM_extractPoints()`	Extract point locations from DEM raster to pass to `BioSIM` functions
`BioSIM_getMPBSLR()`	Get annual historic and projected MPB climate suitability maps from `BioSIM`
`BioSIM_getWindAnnual()`	Get annual historic and projected wind maps from `BioSIM`
`BioSIM_getWindMonthly()`	Get monthly historic and projected wind maps from `BioSIM`
`CASFRItoSpRasts()`	`CASFRItoSpRasts`
`Colors()`	Helper for setting Raster or `SpatRaster` colors
`FireDisturbance()` `FireDisturbancePM()` `PeatlandThermokarst()`	Disturbance functions
`LANDISDisp()`	Simulate a LANDIS-II dispersal process on a landscape.
`makeVegTypeMap()` `loadkNNSpeciesLayersValidation()` `prepSpeciesLayers_KNN2011()`	Make a vegetation type map from a stack of species abundances
`LandR` `LandR-package`	`LandR` package
`NAcover2zero()`	Convert `NA` values in `speciesLayers` to zeros
`Ward()`	Ward Dispersal Kernel -- vectorized, optimized for speed
`addNoPixel2CohortData()`	Add number of pixels per `pixelGroup` and add it has a new column to `cohortData`
`addPixels2CohortData()`	Generate `cohortData` table per pixel:
`aggregateRasByDT()`	Aggregate a raster
`asInteger()`	Convert numeric values to rounded integers
`assertPostPartialDist()`	Assert post-fire disturbance mortality and regeneration
`assert1()` `assert2()` `assertSppMaxBMaxANPP()` `assertUniqueCohortData()` `assertERGs()` `assertColumns()` `assertCohortData()` `assertPixelCohortData()` `assertSpeciesPlotLabels()` `assertFireToleranceDif()` `assertSpeciesLayers()` `assertRstLCChange()` `assertSpeciesEcoregionCohortDataMatch()` `assertPixelCohortDataValid()` `assertRepsAllCohortData()` `assertStandAgeMapAttr()` `assertCohortDataAttr()` `assertSppVectors()` `assertSpeciesTableRaw()` `assertSpeciesTable()`	Assertions
`assignLightProb()`	Assign light probability
`biomodEnsembleFrcstWrapper()`	Simple wrapper around `biomod2::BIOMOD_EnsembleForecasting()`
`biomodEnsembleProjMaps()`	Make maps from `BIOMOD_EnsembleForecasting()` results
`biomodEnsembleWrapper()`	BIOMOD_EnsembleModeling wrapper
`biomodModelingWrapper()`	BIOMOD_Modeling wrapper
`biomodProjWrapper()`	BIOMOD_Projection wrapper
`calcSeverityB()`	Calculate fire severity
`calcSiteShade()`	Calculate site shade
`calculateClimateEffect()`	Null climate effect
`checkSpeciesTraits()`	Check if all species in have trait values
`columnsForPixelGroups`	Default columns that define pixel groups
`.compareRas()` `.compareCRS()`	Compare raster properties
`convertUnwantedLCC()`	Convert Land Cover Classes (LCC) to another value in its neighbourhood
`convertUnwantedLCC2()`	Convert Land Cover Classes (LCC) to another value in its neighbourhood
`defineFlammable()`	Define flammability map
`describeCohortData()`	Summary for `cohortData`
`doResprouting()`	Activate resprouting after a (fire) disturbance
`doSerotiny()`	Activate serotiny after a (fire) disturbance
`.MLLMaxBPartialPlotData()`	Prepare data for model plotting
`.MLLMaxBplotData()`	Prepare data for model plotting
`.fitNLMwCovariates()`	Fit non-linear growth model under various starting conditions
`.getMaxBCoefs()`	Get maximum biomass coefficient names
`.interpolateLightProb()`	Find interpolated value of light probability
`dropTerm()`	Drop factor term including interactions from a model formula
`makeDummyEcoregionMap()` `makeDummyRawBiomassMap()` `makeDummyStandAgeMap()` `makeDummyRstLCC()` `makeDummyEcoregionFiles()`	Create dummy inputs for test simulations
`ecoregionProducer()`	Make `ecoregionMap` and `ecoregion` table
`equivalentName()` `equivalentNameColumn()`	Return equivalent name from a `data.frame` of equivalencies
`extractMaxB()`	Maximum biomass estimator
`fasterizeFromSp()`	Rasterize polygons using `fasterize`
`fitNLMModels()`	FUNCTIONS TO FIT NON-LINEAR MODELS TO ESTIMATE MAXB Wrapper function to fit non-linear growth model per species.
`genPGsPostDisturbance()`	Re-generate new `pixelGroup`s in partially disturbed pixels.
`generatePixelGroups()`	Add the correct `pixelGroups` to a `pixelDataTable` object
`genericExtract()`	Generic extract points
`getWildfire_NFI()`	Download and prepare raster fire data from NFI
`ggplotMLL_maxB()`	Plot estimated maximum biomass by age
`installBioSIM()`	Install BioSIM to retrieve climate and other projections using `BioSIM`
`loadCASFRI()`	Load CASFRI data
`loadkNNSpeciesLayers()`	Load kNN species layers from online data repository
`makeAndCleanInitialCohortData()`	Generate initial `cohortData` table
`makeBiomassMap()`	Create `biomassMap`
`makeCohortDataFiles()`	Make the `cohortData` table, while modifying the temporary `pixelCohortData` that will be used to prepare other files.
`makeEcoregionDT()`	Make the `ecoregion` table
`makeEcoregionMap()`	Make the `ecoregionMap` raster
`makeMinRelativeB()`	Create `minRelativeB` table
`makePickellStack()`	`makePickellStack`
`makePixelGroupMap()`	Create `makePixelGroupMap`
`makePixelTable()`	Make `pixelTable` from biomass, age, land-cover and species cover data
`makeSpeciesEcoregion()`	Create `speciesEcoregion`
`minRelativeBDefaults()`	minRelativeB defaults for Western Boreal Forest Canada
`modifySpeciesAndSpeciesEcoregionTable()`	Update `species` and `speciesEcoregion` tables
`nonForestedPixels()`	Assess non-forested pixels based on species cover data and land-cover
`overlayLCCs()`	Overlay different LCC data sources
`overlayStacks()`	Overlay layers within raster stacks
`partialggplotMLL_maxB()`	Partial effect plots of maximum biomass estimates by age
`partitionBiomass()`	Partition biomass according to cover estimates
`pixelFate()`	Create or amend data to a `pixelFateDT` object
`plantNewCohorts()`	Create new cohorts based on provenance table with unique `pixelGroup` and add to `cohortData`
`plotLeadingSpecies()`	Leading species plots
`plotSpatial()`	Create a `ggplot` of a raster or `sf` object.
`plotVTM()`	Summary plots of leading vegetation types
`prepEcoregions()`	Prepare ecoregions objects
`prepEcozonesRst()`	Prepare ecozones raster
`prepInputsCanDEM()`	Get digital elevation map of Canada
`prepInputsEcoregion()`	Prepare ecoregion table
`prepInputsFireYear()`	Create a raster of fire perimeters
`prepInputsLCC()`	Simple `prepInputs` for Canadian LCC data
`prepInputsSpecies()` `prepInputsMainInput()`	Download and prepare a species traits table for use with `Biomass_core` module
`prepInputsSpeciesEcoregion()`	Prepare species ecoregion table
`prepInputsStandAgeMap()`	Create `standAgeMap`
`prepInputs_NTEMS_LCC_FAO()`	Obtain an LCC layer for a given year from NTEMS, with forest matching the FAO definition
`prepInputs_NTEMS_Nonforest()`	Reclassify non-flammable pixels that become flammable - herbaceous or shrubby - vegetation
`prepRasterToMatch()`	Create `rasterToMatch` and `rasterToMatchLarge`
`prepRawBiomassMap()`	Create `rawBiomassMap`
`prepSpeciesLayers_KNN()` `prepSpeciesLayers_CASFRI()` `prepSpeciesLayers_Pickell()` `prepSpeciesLayers_ForestInventory()` `prepSpeciesLayers_MBFRI()` `prepSpeciesLayers_ONFRI()`	Prepare species layers
`randomStudyArea()`	Create default study areas for use with LandR modules
`rasterRead()`	Wrapper to read a raster using a specific package function
`.NAvalueFlag()` `.stack()` `.projectExtent()` `asInt()` `isInt()` `reclass()`	Set NA values in `Raster` or `SpatRaster`
`replaceAgeInFires()`	Replace stand age with time since last fire
`rescale()`	Rescale function (as in `scales::rescale`)
`rmMissingCohorts()`	Remove missing cohorts from `cohortData` based on `pixelGroupMap`
`scheduleDisturbance()`	Test whether disturbance should be scheduled
`speciesEcoregionLatestYear()`	Pull out the values from `speciesEcoregion` table for current time
`speciesEcoregionStack()`	Create Stacks of the `speciesEcoregion` content
`speciesPresentFromKNN()` `speciesInStudyArea()`	Make a species factor raster
`getSpeciesTable()` `prepSpeciesTable()`	Download and prepare a species traits table for use with `Biomass_core` module
`speciesTableUpdate()`	Change species table of parameters/traits
`sppColors()`	Create species colour vector from a `sppEquiv` table
`sppEquivCheck()`	Check and expand `sppEquiv`
`sppEquivalencies_CA`	Table of species name equivalencies for Canadian trees
`sppHarmonize()`	Harmonize the three components that bring species into `Biomass_**` modules
`standAgeMapGenerator()`	Produce stand age map based on `cohortData`
`statsModel()`	The generic statistical model to run (`lmer` or `glmer`)
`subsetDT()`	Subset a `data.table` with random subsampling within `by` groups
`sumRastersBySpecies()`	Function to sum rasters of species layers
`uniqueCohortDefinition` `uniqueSpeciesEcoregionDefinition`	The columns in a `cohortData` that define "unique"
`updateCohortData()` `.initiateNewCohorts()`	Add cohorts to `cohortData` and `pixelGroupMap`
`updateCohortDataPostHarvest()`	Add cohorts to `cohortData` and `pixelGroupMap`
`updateSpeciesTable()`	Customize species trait table values
`vegTypeGenerator()`	Generate and add vegetation type column to `cohortData`
`vegTypeMapGenerator()`	Generate vegetation type map

Reference

All functions