Automatic discrimination of snow and ice cover types

Calculates the Normalized Difference Snow Ice Index (NDSII) (Keshri et al. 2009) to discriminate between snow and ice surfaces. The discrimination is performed using an automatic threshold selection method based on the Otsu algorithm (Otsu 1979) .

Usage

snow_or_ice(green, NIR)

Arguments

green

SpatRaster. Green band surface reflectance (0.53-0.59 um).

NIR

SpatRaster. Near-infrared band surface reflectance (0.85-0.88 um).

Value

Returns a list with two objects. The first component is an NDSII SpatRaster and the second component provides the optimal threshold to discriminate between snow and ice surfaces.

References

Keshri AK, Shukla A, Gupta RP (2009). “ASTER ratio indices for supraglacial terrain mapping.” International Journal of Remote Sensing, 30(2), 519–524. doi:10.1080/01431160802385459 .

Otsu N (1979). “A Threshold Selection Method from Gray-Level Histograms.” IEEE Transactions on Systems, Man, and Cybernetics, 9(1), 62–66. doi:10.1109/TSMC.1979.4310076 .

See also

preproc(), EBImage::otsu(), terra::plot()

Examples

green <- system.file("extdata/athabasca_B03_20200911.tif", package = "SatRbedo")
nir <- system.file("extdata/athabasca_B8A_20200911.tif", package = "SatRbedo")
outline <- system.file("extdata/athabasca_outline.shp", package = "SatRbedo")
green <- preproc(grd = green, outline = outline)
nir <- preproc(grd = nir, outline = outline)
res <- snow_or_ice(green, nir)

# Plot NDSII
library(terra)
plot(res$NDSII, range = c(-0.5, 0.5))


# Plot a cover type binary map (snow/ice)
library(terra)
plot(res$NDSII > res$th, type = "classes", col = c("#FFFFC8", "#00407F"), levels = c("snow", "ice"))