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Mask a dataset from a QA band.

mask.Rd

Derive a bad-pixel mask from a named QA band, optionally clean it with binary morphology, set bad pixels to NaN (nodata) on every value band, and drop the QA band. The mask is a shared subgraph computed once per slice and reused across all value bands.

Usage

mask(
  x,
  from = NULL,
  where,
  open = 0L,
  dilate = 0L,
  drop = TRUE,
  join = "exact"
)

Arguments

x

A LazyDataset.

from

QA band to derive the mask from; defaults to the dataset's mask_asset.

where

The removal predicate (mask where TRUE). One of:

  • a numeric vector -> value membership (bad if the pixel value is in the set), for categorical QA such as Sentinel-2 SCL, e.g. c(0, 1, 2, 3, 8, 9, 10, 11);

  • qa_bits() -> a bitmask test (bad if any listed bit is set), for packed flags such as HLS Fmask / Landsat QA_PIXEL, e.g. qa_bits(0:3);

  • a function \(f) ... -> a predicate returning a 0/1 (or logical) mask, written in the g_* vocabulary.

open

Opening radius (despeckle): erosion then dilation at this radius, removing isolated flagged pixels up to the radius. 0 skips it.

dilate

Dilation radius (buffer): grows the surviving bad regions outward, a safety margin around clouds. 0 skips it. Applied after open.

drop

Drop the QA band from the returned dataset? (default TRUE.)

join

How value and mask slices pair when both carry slice names that do not fully align: "exact" (default) aborts; "inner" pairs on the shared slice names and reports what dropped.

Value

A LazyDataset with masked value bands.