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Visualize by extracted exposure

Source: R/fire_exp_extract_vis.R
fire_exp_extract_vis.Rd

fire_exp_extract_vis() standardizes the visualization of outputs from fire_exp_extract() as a summary table or a map by classifying exposure into predetermined exposure classes.

Landscape classification breaks are:

  • Low (0-20%)

  • Moderate (20-40%)

  • High (40-60%),

  • Very High (60-80%)

  • Extreme (80-100%)

Local classification breaks are:

  • Nil (0%)

  • Low (>0-15%)

  • Moderate (15-30%)

  • High (30-45%)

  • Extreme (45%+)

Usage

fire_exp_extract_vis(
  values_ext,
  method = c("max", "mean"),
  classify = c("local", "landscape"),
  map = FALSE
)

Arguments

values_ext

Spatvector of points or polygons from fire_exp_extract()

method

character, either "max" or "mean". If values_ext are polygons the default is "max".This parameter is ignored when values_ext are point features.

classify

character, either "local" or "landscape" to specify classification scheme to use. The default is "local"

map

Boolean. When TRUE, a map is returned as a ggplot object. The default is FALSE.

Value

a summary table is returned as a data frame object, Unless: map = TRUE: a ggplot object

Examples

# read example hazard data ----------------------------------
filepath <- "extdata/hazard.tif"
haz <- terra::rast(system.file(filepath, package = "fireexposuR"))
# read example AOI polygon geometry
filepath <- "extdata/builtsimpleexamplegeom.csv"
g <- read.csv(system.file(filepath, package = "fireexposuR"))
v <- terra::vect(as.matrix(g), "polygons", crs = haz)
# generate random points within polygon
pts <- terra::spatSample(v, 200)
# ----------------------------------------------------------

exp <- fire_exp(haz)

vals_exp <- fire_exp_extract(exp, pts)

# summarize example points in a table
fire_exp_extract_vis(vals_exp, classify = "local")
#>   scale method    class   n prop
#> 1 local  Point      Nil 144 0.72
#> 2 local  Point      Low  26 0.13
#> 3 local  Point Moderate  10 0.05
#> 4 local  Point     High  10 0.05
#> 5 local  Point  Extreme  10 0.05

# visualize example points in standardized map
fire_exp_extract_vis(vals_exp, map = TRUE)