maskInvarFeatures: Identify pseudo-invariant features from a satellite scene

In environmentalinformatics-marburg/satellite: Handling and Manipulating Remote Sensing Data

Identify pseudo-invariant features from a satellite scene

Description

Identify pseudo-invariant features from a satellite scene based on a vis, near infravis and short-wave infravis band.

Usage

## S4 method for signature 'Satellite'
maskInvarFeatures(x)

## S4 method for signature 'RasterStack'
maskInvarFeatures(x, quant = 0.01, id_vis = 1L, id_nir = 2L, id_swir = 3L)

## S4 method for signature 'RasterLayer'
maskInvarFeatures(x, nir, swir, quant = 0.01)

Arguments

x	A Satellite object or a raster::RasterLayer providing the sensor's vis band.
quant	A value v = [0...1] which is used to define the percentage threshold values (thv) for invariant features (nir/vis ratio < thv, swir band values > 1-thv).
id_vis	Index of the visible band.
id_nir	Index of the near infravis band.
id_swir	Index of the short-wave infravis band.
nir	A raster::RasterLayer containing the sensor's nir band.
swir	A raster::RasterLayer containing the sensor's swir band.

Details

Invariant features are identified as pixels which belong to the group of (i) the n lowest VIS/NIR ratios and of (ii) the highest n SWIR values. The value of n is given by the parameter quant = [0...1].

Value

If x is a Satellite object, a Satellite object with added layer;
if x is a raster::RasterLayer object, a a raster::RasterLayer object with added layers (1 indicates invariant pixels, 0 otherwise).

References

This function is taken and only slightly modified from the PIF function by Sarah C. Goslee (2011). Analyzing Remote Sensing Data in R: The landsat Package. Journal of Statistical Software,43(4), 1-25, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v043.i04")}.

The underlying theory has been published by Schott RJ, Salvaggio C and Volchok WJ (1988) Radiometric scene normalization using pseudoinvariant features. Remote Sensing of Environment 26/1, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/0034-4257(88)90116-2")}.

Examples

path <- system.file("extdata", package = "satellite")
files <- list.files(path, pattern = glob2rx("LC08*.TIF"), full.names = TRUE)
sat <- satellite(files)
sat <- maskInvarFeatures(sat)

maskInvarFeatures(x = getSatDataLayer(sat, "B004n"), 
                  nir = getSatDataLayer(sat, "B005n"), 
                  swir = getSatDataLayer(sat, "B007n"))

## when dealing with a 'RasterStack'
rst <- stack(files[c(6, 7, 9)])
maskInvarFeatures(rst)

environmentalinformatics-marburg/satellite documentation built on Feb. 10, 2024, 2:56 p.m.