sample_raster: Generate random sample polygons from a raster layer,...
In azvoleff/teamlucc: TEAM land use and cover change data processing toolkit

Description Usage Arguments Value Examples

Useful for gathering training data for an image classification. With the default settings, the output polygons will be perfectly aligned with the pixels in the input raster.

1 2	sample_raster(x, size, strata = NULL, side = xres(x), fields = c(), na.rm = TRUE, exp = 5)

`x`	a `Raster*`
`size`	the sample size (number of sample polygons to return)
`strata`	(optional) a `RasterLayer` of integers giving the strata of each pixel (for example, a classified image)
`side`	desired length for each side of the sample polygon (units of the input `Raster*`, usually meters)
`fields`	a list of fields to include in the output `SpatialPolygonsDataFrame` (such as a "class" field if you will be digitizing classes).
`na.rm`	whether to remove pixels with NA values from the sample
`exp`	multiplier used to draw larger initial sample to account for the loss of sample polygons lost because they contain NAs, and, for stratified sampling, to account for classes that occur very infrequently in the data. Increase this value if the final sample has fewer sample polygons than desired.

a SpatialPolygonsDataFrame

## Not run: 
set.seed(0)
L5TSR_1986_b1 <- raster(L5TSR_1986, layer=1)
training_polys <- sample_raster(L5TSR_1986_b1, 30,
                                  side=6*xres(L5TSR_1986_b1))
plot(L5TSR_1986_b1)
plot(training_polys, add=TRUE)

## End(Not run)