Sample a raster stack by map unit polygons, at a constant density.
sampleRasterStackByMU(mu, mu.set, mu.col, raster.list, pts.per.acre, p = c(0, 0.05, 0.25, 0.5, 0.75, 0.95, 1), progress = TRUE, estimateEffectiveSampleSize=TRUE, polygon.id='pID')
character vector of map unit labels to be sampled
column name in attribute table containing map unit labels
target sampling density in `points per acre`
percentiles for polygon area stats, e.g. (0.05, 0.25, 0.5, 0.75, 0.95)
logical, print a progress bar while sampling?
estimate an effective sample size via Moran's I?
Column name containing unique polygon IDs; default: 'pID'; calculated if missing
This function is used by various NRCS reports that summarize or compare concepts defined by collections of polygons using raster data sampled from within each polygon, at a constant sampling density. Even though the function name includes "rasterSTack", this function doesn't actually operate on a `stack` object as defined in the raster package. The collection of raster data defined in
raster.list do not have to share a common coordinate reference system, grid spacing, or extent. Point samples generated from
mu are automatically converted to the CRS of each raster before extracting values. The extent of each raster in
raster.list must completely contain the extent of
data.frame containing samples from all rasters in the stack
data.frame containing area statistics for all map units in the collection
an index to rows in the original SPDF associated with polygons not sampled
data.frame containing information on sampled rasters
data.frame containing estimates Moran's I (index of spatial autocorrelation)