RStoolbox (version 0.1.6)

classifyQA: Classify Landsat8 QA Band

Description

extracts five classes from QA band: background, cloud, cirrus, snow and water.

Usage

classifyQA(img, type = c("background", "cloud", "cirrus", "snow", "water"), confLayers = FALSE, ...)

Arguments

img

RasterLayer. Landsat 8 OLI QA band.

type

Character. Classes which should be returned. One or more of c("background", "cloud", "cirrus","snow", "water").

confLayers

Logical. Return one layer per class classified by confidence levels, i.e. cloud:low, cloud:med, cloud:high.

...

further arguments passed to writeRaster

Value

Returns a RasterLayer with maximal five classes:

class

value

background

1L

cloud

2L

cirrus

3L

snow

4L

water

5L

Values outside of these classes are returned as NA. If confLayers = TRUE then a RasterStack with one layer per condition (except 'background') is returned, whereby each layer contains the confidence level of the condition.

Confidence

value

low

1L

med

2L

high

3L

Details

By default each class is queried for *high* confidence. See encodeQA for details. To return the different confidence levels per condition use confLayers=TRUE. This approach corresponds to the way LandsatLook Quality Images are produced by the USGS.

See Also

encodeQA decodeQA

Examples

library(raster)
qa <- raster(ncol = 100, nrow=100, val = sample(1:2^14,  10000))

## QA classes
qacs <- classifyQA(img = qa)
## Confidence levels
qacs_conf <- classifyQA(img = qa, confLayers = TRUE)