This function enables to produce a map of
the AGBD and associated uncertainty, using a spatially varying coefficient
calibrated model created with the calibrate_model() function.
Usage
predict_map(
fit_brms,
pred_raster,
grid_size,
raster_fun = mean,
n_cores = getOption("mc.cores", 1),
n_post_draws = 50,
alignment_raster = NULL,
plot_maps = TRUE
)Arguments
- fit_brms
a brmsfit object, output of the
calibrate_model()function.- pred_raster
filename (character) or a SpatRaster object from terra package: the raster to predict using fit_brms (typically a CHM raster created from LiDAR data)
- grid_size
a numeric indicating the dimension of grid cells. Must be identical to 'grid_size' used in
divide_plot()- raster_fun
the function to apply to summarize the values of 'pred_raster'. Must be identical to 'raster_fun' used in
subplot_summary()- n_cores
number of cores to use for predictions
- n_post_draws
positive integer indicating how many posterior draws should be used
- alignment_raster
filename (character) or a SpatRaster object from terra package: a raster whose coordinates will be used to align the coordinates of the predicted raster.
- plot_maps
A logical indicating whether the maps should be displayed (median, sd and CV of AGBD posterior distributions)
Value
The data-table format of 'pred_raster', to which the following variables have been added:
post_median_AGBD: the median of the posterior distributions of the predicted AGBDs
post_sd_AGBD: the sd of the posterior distributions of the predicted AGBDs
post_cred_2.5_AGBD and post_cred_97.5_AGBD: the 2.5 and 97.5 quantiles of the posterior distributions of the predicted AGBDs