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)

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

Arguments

x	raster class object
trans	Transformation method: "norm", "rstd", "std", "stretch", "nl", "slog", "sr" (please see notes)
smin	Minimum value for stretch
smax	Maximum value for stretch

Value

raster class object of transformation

Author

Jeffrey S. Evans jeffrey_evans@tnc.org

Examples

# \donttest{
  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) ) 
   }
#> applying normalization transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 0, 1  (min, max)
#> 
#> applying row-standardization transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 0.40009, 1  (min, max)
#> 
#> applying standardization transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : -1.739012, 1.722989  (min, max)
#> 
#> applying stretch transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 0, 255  (min, max)
#> 
#> applying log transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 6.907824, 7.823889  (min, max)
#> 
#> applying singned-log10 transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 3.00003, 3.397872  (min, max)
#> 
#> applying sqare-root transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 31.62386, 49.99609  (min, max)
#> 

 # 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) ) ) 
   }
#> [1] " Min value < 0, running row standardization instead"
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : -1.000017, 1  (min, max)
#> 
#> applying row-standardization transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : -1.000017, 1  (min, max)
#> 
#> applying standardization transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : -1.718704, 1.742859  (min, max)
#> 
#> applying stretch transformation
#> class      : RasterLayer 
#> dimensions : 100, 100, 10000  (nrow, ncol, ncell)
#> resolution : 449.4, 301.5  (x, y)
#> extent     : 571823, 616763, 4423540, 4453690  (xmin, xmax, ymin, ymax)
#> crs        : NA 
#> source     : memory
#> names      : layer 
#> values     : 0, 255  (min, max)
#> 
#> Error in h(simpleError(msg, call)) : 
#>   error in evaluating the argument 'x' in selecting a method for function 'print':  Minimum value < 0, cannot log transform
#> Error in h(simpleError(msg, call)) : 
#>   error in evaluating the argument 'x' in selecting a method for function 'print':  Minimum value < 0, cannot log transform
#> Error in h(simpleError(msg, call)) : 
#>   error in evaluating the argument 'x' in selecting a method for function 'print':  Minimum value < 0, cannot log transform
# }