raster.transformation

Statistical transformation for rasters

Transforms raster to a specified statistical transformation

Transformation option details:

• norm - (Normalization_ (0-1): if min(x) < 0 ( x - min(x) ) / ( max(x) - min(x) )

• rstd - (Row standardize) (0-1): if min(x) >= 0 x / max(x) This normalizes data

•    with negative distributions
  

• std - (Standardize) (x - mean(x)) / sdv(x)

• stretch - (Stretch) ((x - min(x)) * max.stretch / (max(x) - min(x)) + min.stretch) This will stretch values to the specified minimum and maximum values (eg., 0-255 for 8-bit)

• nl - (Natural logarithms) if min(x) > 0 log(x)

• slog - (Signed log 10) (for skewed data): if min(x) >= 0 ifelse(abs(x) <= 1, 0, sign(x)*log10(abs(x)))

• sr - (Square-root) if min(x) >= 0 sqrt(x)

Usage

raster.transformation(x, trans = "norm", smin = 0, smax = 255)

Aliases

• raster.transformation

Examples

# NOT RUN {
  library(raster)
  r <- raster(nrows=100, ncols=100, xmn=571823, xmx=616763, 
              ymn=4423540, ymx=4453690)
    r[] <- runif(ncell(r), 1000, 2500)

 # Postive values so, can apply any transformation    
for( i in c("norm", "rstd", "std", "stretch", "nl", "slog", "sr")) {
  print( raster.transformation(r, trans = i) ) 
   }

 # Negative values so, can't transform using "nl", "slog" or "sr"
r[] <- runif(ncell(r), -1, 1)
   for( i in c("norm", "rstd", "std", "stretch", "nl", "slog", "sr")) {
  try( print( raster.transformation(r, trans = i) ) ) 
   }
# }
# NOT RUN {
# }