bExplore | R Documentation |
Explore backscatter layer statistics and relationships prior to harmonization to inform the bulk shift procedure.
bExplore(
x,
y,
preds = NULL,
error_map = TRUE,
boxplot = TRUE,
error_plot = TRUE,
loess = TRUE,
loess_samp = 10000,
...
)
x, y |
terra SpatRasters. Backscatter layers to compare. |
preds |
terra SpatRaster. Predictors to explore for explaining error between |
error_map |
Logical. Whether to plot a map of error between |
boxplot |
Logical. Whether to draw boxplots comparing |
error_plot |
Logical. Whether to plot the error as a function of |
loess |
Logical. Whether to use loess to visualized the relationship between |
loess_samp |
Numeric. Maximum number of samples used to estimate the loess smoother. See Details. |
... |
Additional arguments to pass to loess. See Details. |
This function creates a series of helpful plots for comparing backscatter datasets prior to attempting harmonization (e.g., using bulkshift). Hit enter to proceed through the plots.
boxplot = TRUE
draws box plots comparing the full distributions of x and y, and also the distributions only where they overlap. This
is useful for assessing the representativeness of the area overlap (i.e., whether the error model will need to extrapolate).
Local polynomial fitting using loess can be slow with large sample sizes. Subsampling using loess_samp
is used here only to fit
the smoother; it is predicted on the entire dataset. Additional arguments can be passed to ...
(see loess for more information).
bb2016 <- rast(system.file('extdata', 'bb2016.tif', package='bulkshift'))
bb2017 <- rast(system.file('extdata', 'bb2017.tif', package='bulkshift'))
bbdepth <- rast(system.file('extdata', 'bbdepth.tif', package='bulkshift'))
bExplore(bb2017, bb2016, preds = bbdepth)
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