fireSense_spreadPredict Module

(ref:fireSense-spreadPredict) fireSense_spreadPredict

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Authors:

Eliot McIntire [aut, cre], Tati Micheletti [aut], Ian Eddy [aut], Jean Marchal [aut], Alex M. Chubaty [ctb]

Module Overview

Module summary

Each year, predicts a raster of fire spread probabilities from the parameters fitted by fireSense_spreadFit, for the spread component of fireSense [@Marchal:2017a; @Marchal:2017b; @Marchal:2019].

  1. The covariates in fireSense_SpreadCovariates are rescaled to [0, 1] using covMinMax_spread, the range of the fitting data.
  2. With the one parameter set (row of studyAreaWithSpreadParams$params[[i]]) chosen by .rep, i.e. row ((rep - 1) %% number of sets) + 1 of each ELF, the spread probability is a 2- or 3-parameter logistic of the linear combination of the covariates, with lower asymptote lowerSpreadProb.
  3. fireSense_SpreadPredicted is that single set’s prediction (sets are not averaged), and fireSense_SpreadSD its yearSpreadSD, on the flammableRTM grid.

Module inputs and parameters

studyAreaWithSpreadParams (the fitted parameters, from fireSense_spreadFit) is read from the simList though it is not declared as an input. Prediction uses the covariates the fit has coefficients for, not the terms of fireSense_spreadFormula; each must be a column of fireSense_SpreadCovariates. The module stops if studyAreaWithSpreadParams has no parameters. maxFireSpread must have the same value in every module that defines it.

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

(#tab:moduleInputs-fireSense-spreadPredict)(#tab:moduleInputs-fireSense-spreadPredict)List of (ref:fireSense-spreadPredict) input objects and their description.
objectName objectClass desc sourceURL
covMinMax_spread data.table Minimum and maximum (2 rows) of each covariate in the fitting data, used to rescale the covariates as in fireSense_spreadFit. NA
fireSense_SpreadCovariates data.table This year’s covariates, from fireSense_dataPrepPredict. pixelID is the cell index of flammableRTM. NA
rasterToMatchLargeELF SpatRaster Only with several fitted ELFs: each pixel’s ELF (ELFind), on the grid of flammableRTM, from fireSense_ELFs with a studyAreaLarge. NA
flammableRTM SpatRaster Binary raster, 1 where the pixel is flammable. Template for fireSense_SpreadPredicted. NA

Summary of user-visible parameters (Table @ref(tab:moduleParams-fireSense-spreadPredict))

(#tab:moduleParams-fireSense-spreadPredict)(#tab:moduleParams-fireSense-spreadPredict)List of (ref:fireSense-spreadPredict) parameters and their description.
paramName paramClass default min max paramDesc
lowerSpreadProb numeric 0.13 NA NA Lower asymptote of the 2- and 3-parameter logistic. Default fireSenseUtils::spreadProbFloor, the same constant fireSense_spreadFit fits with.
ELFblendWidth numeric 20000 NA NA With several ELFs: each ELF’s model also predicts this far (m) outside its own pixels, and where predictions overlap they are averaged with weights that fall linearly from 1 inside the ELF to 0 at this distance outside it. 50/50 at a boundary. The default is the buffer fireSenseUtils::makeELFs() puts around ELFs.
maxFireSpread numeric 0.276 NA NA Upper limit on spreadProb used when fitting (default fireSenseUtils::spreadProbCeiling). Here it is only checked to be the same in every module that defines it.
.rep integer 1 1 NA Which replicate this prediction is. It selects parameter set ((rep - 1) %% number of sets) + 1 of each ELF, so replicates cycle through the fitted sets, each used whole (with its own yearSpreadSD), never averaged.
.runInitialTime numeric 0 NA NA Time of the first prediction.
.runInterval numeric 1 NA NA Interval between predictions, in years. NA predicts once.
.saveInitialTime numeric NA NA NA Time of the save event, which does nothing. NA means never.
.studyAreaName character NA NA NA Human-readable name for the study area used.
.useCache logical FALSE NA NA Should this entire module be run with caching activated? This is generally intended for data-type modules, where stochasticity and time are not relevant

Events

  • init: checks maxFireSpread against the other modules; schedules run at .runInitialTime, and save at .saveInitialTime if that is not NA.
  • run: makes the prediction described above; repeats every .runInterval.
  • save: does nothing, and says so in a message.

The module does not plot anything.

Module outputs

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

(#tab:moduleOutputs-fireSense-spreadPredict)(#tab:moduleOutputs-fireSense-spreadPredict)List of (ref:fireSense-spreadPredict) outputs and their description.
objectName objectClass desc
fireSense_SpreadPredicted SpatRaster Spread probability of each flammable pixel, this year.
fireSense_SpreadSD SpatRaster|numeric The fitted sd of the per-year random effect on logit spread probability (yearSpreadSD of the parameter set chosen by .rep; 0 if the fit has none), for fireSense_burn. One number with one fitted ELF; with several, a raster blended across ELFs with the weights of fireSense_SpreadPredicted.

Runs after fireSense_dataPrepPredict (covariates) and fireSense_spreadFit (parameters). fireSense_SpreadPredicted is used by fireSense_burn to spread fires. It is normally run as part of the fireSense module group.

Getting help

References