## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----out.width = "850px", echo=FALSE------------------------------------------ knitr::include_graphics("flowchart.png") ## ----example1, eval = FALSE--------------------------------------------------- # # Load the fireexposuR library # library(fireexposuR) # # # Load the terra library for reading/writing spatial data # library(terra) # # # read raster of wildland fuels hazardous for long-range ember transmission # hazard_long <- rast("long_range_hazard.tif") # # # read raster of wildland fuels hazardous for short-range ember transmission # hazard_short <- rast("short_range_hazard.tif") # # # compute long-range ember exposure using the long-range hazard layer # exposure_long <- fire_exp(hazard_long, tdist = "l") # # # compute short-range ember exposure using the short-range hazard layer # exposure_short <- fire_exp(hazard_short, tdist = "s") # # # Export the results as a .tif file using terra # writeRaster(exposure_long, "exposure_long.tif") # writeRaster(exposure_short, "exposure_short.tif") ## ----example2, eval = FALSE--------------------------------------------------- # # Load the fireexposuR library # library(fireexposuR) # # # Load the terra library for reading/writing spatial data # library(terra) # # # # PLEASE NOTE: The following code is to demonstrate an example workflow. The # # referenced input data does not exist. # # # read raster of wildland fuels hazardous for long-range ember transmission # hazard_long <- rast("long_range_hazard.tif") # # # compute long-range ember exposure using the long-range hazard layer # exposure_long <- fire_exp(hazard_long, tdist = "l") # # # read point feature vector of a single value location # point_value <- vect("point_value.shp") # # # read point feature vector of value locations # multiple_values <- vect("multiple_values.shp") # # # assess directional exposure for a single point # transects_point <- fire_exp_dir(exposure_long, point_value) # # # export the transects for the point feature as a shapefile with terra # writeVector(transects_point, "transects_point.shp") # # # loop through multiple values and export the results as shapefiles # for (i in seq_len(nrow(multiple_values))) { # dir_exp_point <- fire_exp_dir(exposure_long, multiple_values[i]) # # set a file name based on the feature row number # file_name <- paste("transects_point_", i, ".shp", sep = "") # writeVector(dir_exp_point, file_name) # } ## ----example3, eval = FALSE--------------------------------------------------- # # Load the fireexposuR library # library(fireexposuR) # # # Load the terra library for reading/writing spatial data # library(terra) # # # PLEASE NOTE: The following code is to demonstrate an example workflow. The # # referenced input data does not exist. # # # read raster of wildland fuels hazardous for long-range ember transmission # hazard_long <- rast("long_range_hazard.tif") # # # read raster of wildland fuels hazardous for short-range ember transmission # hazard_short <- rast("short_range_hazard.tif") # # # compute long-range ember exposure using the long-range hazard layer # exposure_long <- fire_exp(hazard_long, tdist = "l") # # # compute short-range ember exposure using the short-range hazard layer # exposure_short <- fire_exp(hazard_short, tdist = "s") # # # read polygon feature vector of an area of interest boundary # # (e.g., a built environment) # area_of_interest <- vect("area_of_interest.shp") # # # read point feature vector of value locations # # (e.g., structures in a community) # multiple_values <- vect("multiple_values.shp") # # # extract the underlying long-range ember exposure to values attributes # values_exposure_long <- fire_exp_extract(exposure_long, multiple_values) # # # extract the underlying short-range ember exposure to values attributes # values_exposure_short <- fire_exp_extract(exposure_short, multiple_values) # # # Visualize short-range ember exposure classes in the aoi with a summary table # fire_exp_summary(exposure_long, area_of_interest, classify = "local") # # # Visualize long-range ember exposure classes in the aoi with a map # fire_exp_map_class(exposure_long, area_of_interest, classify = "local") # # # Visualize long-range ember exposure classes to values in summary table # fire_exp_extract_vis(values_exposure_long, classify = "local") # # # Visualize long-range ember exposure classes to values in map # fire_exp_extract_vis(values_exposure_long, classify = "local", map = TRUE) # # # Repeat the visualizations for short-range ember exposure # fire_exp_summary(exposure_short, area_of_interest, classify = "local") # fire_exp_map_class(exposure_short, area_of_interest, classify = "local") # fire_exp_extract_vis(values_exposure_short, classify = "local") # fire_exp_extract_vis(values_exposure_short, classify = "local", map = TRUE) ## ----example4a, eval = FALSE-------------------------------------------------- # # Load the fireexposuR library # library(fireexposuR) # # # Load the terra library for reading/writing spatial data # library(terra) # # # PLEASE NOTE: The following code is to demonstrate an example workflow. The # # referenced input data does not exist. # # # read long-range ember hazard raster # hazard <- rast("hazard.tif") # # # read non-burnable landscape raster # no_burn <- rast("no_burn.tif") # # # compute long-range ember exposure # exposure <- fire_exp(hazard, tdist = "l", no_burn = no_burn) # # # read the fire perimeters with terra # fires <- vect("fires.shp") # # # generate validation table, and then plot the results # output <- fire_exp_validate(exposure, fires) # fire_exp_validate_plot(output) ## ----example4b, eval = FALSE-------------------------------------------------- # # Load the fireexposuR library # library(fireexposuR) # # # Load the terra library for reading/writing spatial data # library(terra) # # # PLEASE NOTE: The following code is to demonstrate an example workflow. The # # referenced input data does not exist. # # # read long-range ember hazard raster # hazard <- rast("hazard.tif") # # # read non-burnable landscape raster # no_burn <- rast("no_burn.tif") # # # compute long-range ember exposure for default transmission distance # exposure_a <- fire_exp(hazard, tdist = "l", no_burn = no_burn) # # # compute long-range ember exposure for a custom transmission distance # exposure_b <- fire_exp(hazard, tdist = 800, no_burn = no_burn) # # # read the fire perimeters with terra # fires <- vect("fires.shp") # # # validation tables for both options # output_a <- fire_exp_validate(exposure_a, fires) # output_b <- fire_exp_validate(exposure_b, fires) ## ----example4c, eval = FALSE-------------------------------------------------- # # Load the fireexposuR library # library(fireexposuR) # # # Load the terra library for reading/writing spatial data # library(terra) # # # PLEASE NOTE: The following code is to demonstrate an example workflow. The # # referenced input data does not exist. # # # read long-range ember hazard raster: option A # hazard_a <- rast("hazard_a.tif") # # # read non-burnable landscape raster: option A # no_burn_a <- rast("no_burn_a.tif") # # # read long-range ember hazard raster: option B # hazard_b <- rast("hazard_b.tif") # # # read non-burnable landscape raster: option B # no_burn_b <- rast("no_burn_b.tif") # # # compute long-range ember exposure for option A # exposure_a <- fire_exp(hazard_a, tdist = "l", no_burn = no_burn_a) # # # compute long-range ember exposure for option A # exposure_b <- fire_exp(hazard_b, tdist = "l", no_burn = no_burn_b) # # # read the fire perimeters with terra # fires <- vect("fires.shp") # # # validation tables for both options # output_a <- fire_exp_validate(exposure_a, fires) # output_b <- fire_exp_validate(exposure_b, fires)