image_mask: Create a mask for images in a raster data cube

In gdalcubes: Earth Observation Data Cubes from Satellite Image Collections

Create a mask for images in a raster data cube

Description

Create an image mask based on a band and provided values to filter pixels of images read by raster_cube

Usage

image_mask(
  band,
  min = NULL,
  max = NULL,
  values = NULL,
  bits = NULL,
  invert = FALSE
)

Arguments

band	name of the mask band
min	minimum value, values between min and max will be masked
max	maximum value, values between min and max will be masked
values	numeric vector; specific values that will be masked.
bits	for bitmasks, extract the given bits (integer vector) with a bitwise AND before filtering the mask values, bit indexes are zero-based
invert	logical; invert mask

Details

Values of the selected mask band can be based on a range (by passing min and max) or on a set of values (by passing values). By default pixels with mask values contained in the range or in the values are masked out, i.e. set to NA. Setting invert = TRUE will invert the masking behavior. Passing values will override min and max.

Note

Notice that masks are applied per image while reading images as a raster cube. They can be useful to eliminate e.g. cloudy pixels before applying the temporal aggregation to merge multiple values for the same data cube pixel.

Examples

image_mask("SCL", values = c(3,8,9)) # Sentinel 2 L2A: mask cloud and cloud shadows
image_mask("BQA", bits=4, values=16) # Landsat 8: mask clouds
image_mask("B10", min = 8000, max=65000) 

gdalcubes documentation built on May 29, 2024, 5:11 a.m.