fire_exp_validate {fireexposuR} | R Documentation |
Validate exposure with observed fires
Description
For advanced users. fire_exp_validate()
compares the
proportion of exposure classes in a the study area to the proportion of
exposure classes within observed burned areas.
Usage
fire_exp_validate(
burnableexposure,
fires,
aoi,
class_breaks = c(0.2, 0.4, 0.6, 0.8, 1),
samplesize = 0.005
)
Arguments
burnableexposure |
A SpatRaster of exposure, non-burnable cells should
be removed using optional parameter |
fires |
A SpatVector of observed fire perimeters |
aoi |
(Optional) A SpatVector that delineates an area of interest |
class_breaks |
(Optional) vector of numeric values between 0-1 of the
upper limits of each class. The default is |
samplesize |
Proportion of areas to sample. The default is |
Details
This function automates a simple validation method to assess if fire burns
preferentially in areas with high exposure. The methods, and figure produced
with fire_exp_validate_plot()
, are based on Beverly et al. (2021).
The function requires an exposure raster produced for a past point in time.
Cells that cannot burn, or do not represent natural land cover should be
removed by setting the no_burn
parameter in fire_exp()
or
fire_exp_adjust()
.
The function also requires fire perimeter data. Currently, the function takes the fires as a Vector of polygons because that is typically how fire boundaries are stored in spatial databases. The fires input data should include all of the burned area that has occurred following the time period the input exposure layer was produced for. It is up to the user to determine the appropriate amount of burned area required for a meaningful assessment.
A random sample is taken to account for spatial autocorrelation, the
sampled location results can be used to test for significant differences.
The sample size can be adjusted. The sample size represents a proportion of
cells, the default is 0.005
(0.5%). It is the user's responsibility to set
an appropriate sample size.
The class breaks can be customized from the default of 0.2 intervals by
setting the class_breaks
parameter. A class of Nil is automatically added
for values exactly equal to 0.
Value
a table of number of cells (n) and proportions (prop) of exposure classes within a sampled area (Sample) and across the full extent (Total).for the full extent of the exposure data (expected) and only within the burned areas (observed).
References
Beverly JL, McLoughlin N, Chapman E (2021) A simple metric of landscape fire exposure. Landscape Ecology 36, 785-801. doi:10.1007/s10980-020-01173-8
See Also
Examples
# read example hazard data
hazard_file_path <- "extdata/hazard.tif"
hazard <- terra::rast(system.file(hazard_file_path, package = "fireexposuR"))
# generate example non-burnable cells data
geom_file_path <- "extdata/polygon_geometry.csv"
geom <- read.csv(system.file(geom_file_path, package = "fireexposuR"))
polygon <- terra::vect(as.matrix(geom), "polygons", crs = hazard)
no_burn <- terra::rasterize(polygon, hazard)
# generate example fire polygons by buffering random points
points <- terra::spatSample(terra::rescale(hazard, 0.8),
30, as.points = TRUE)
fires <- terra::buffer(points, 800)
# PLEASE NOTE THIS EXAMPLE DATA DOES NOT GENERATE MEANINGFUL RESULTS
# compute exposure and remove non-burnable cells
exposure <- fire_exp(hazard, no_burn = no_burn)
# validation table
fire_exp_validate(exposure, fires)