spatialEco (version 1.3-2)

raster.change: Raster change between two nominal rasters

Description

Compares two categorical rasters with a variety of statistical options

This function provides a various statistics for comparing two classified maps. Valid options are:

• kappa - Cohen's Kappa

• wkappa - Cohen's Weighted Kappa (not yet implemented)

• t.test - Two-tailed paired t-test

• cor - Persons Correlation

• entropy - Delta entropy

• cross-entropy - Cross-entropy loss function

• divergence - Kullback-Leibler divergence (relative entropy)

Kappa and t-test values < 0 are reported as 0. For a weighted kappa, a matrix must ne provided that correspond to the pairwise weights for all values in both rasters. Delta entropy is derived by calculating Shannon's on each focal window then differencing them (e(x) - e(y))

Usage

raster.change(
  x,
  y,
  d = c(3, 3),
  stat = c("kappa", "wkappa", "t.test", "cor", "entropy", "cross-entropy",
    "divergence"),
  w = NULL,
  out.raster = NULL,
  mask = FALSE,
  force.memory = FALSE
)

Arguments

x

First raster for comparison, rasterLayer class object

y

Second raster for comparison, rasterLayer class object

d

Rectangular window size, must be odd but not necessarily square

stat

Statistic to use in comparison, please see details for options.

w

Weights if stat="kappa", must represent same classes as input rasters

out.raster

Optional output raster

mask

(FALSE/TRUE) mask output to original rasters

force.memory

(FALSE/TRUE) Force in memory processing, may fail with insufficient RAM

Value

A raster layer or stack object one of the following layers:

• kappa Kappa or Weighted Kappa statistic (if stat = "kappa")

• correlation Paired t.test statistic (if stat = "cor")

• entropy Delta entropy (if stat = "entropy")

• divergence Kullback-Leibler divergence (if stat = "divergence")

• cross.entropy Cross-entropy (if stat = "cross.entropy")

• t.test Paired t.test statistic (if stat = "t.test")

• p.value p-value of the paired t.test statistic (if stat = "t.test")

References

Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20:37-46

McHugh M.L. (2012) Interrater reliability: the kappa statistic. Biochemia medica, 22(3):276<U+2013>282.

Kullback, S., R.A. Leibler (1951). On information and sufficiency. Annals of Mathematical Statistics. 22(1):79<U+2013>86

Examples

# NOT RUN {
 library(sp)
 library(raster)
 data(meuse.grid)
 r1 <- sp::SpatialPixelsDataFrame(points = meuse.grid[c("x", "y")], 
                                  data = meuse.grid)
r1 <- raster(r1)
  na.idx <- which(!is.na(r1[]))
  r1[na.idx] <- round(runif(length(na.idx), 1,5),0)
 r2 <- sp::SpatialPixelsDataFrame(points = meuse.grid[c("x", "y")], 
                                  data = meuse.grid) 
r2 <- raster(r2)
  r2[na.idx] <- round(runif(length(na.idx), 1,5),0)
  
s = 11    
 ( r.kappa <- raster.change(r1, r2, d = s, mask = TRUE) )   
 ( r.ttest <- raster.change(r1, r2, d = s, stat="t.test", mask = TRUE) )
 ( r.ent <- raster.change(r1, r2, d = s, stat="entropy", mask = TRUE) )   
 ( r.cor <- raster.change(r1, r2, d = s, stat="cor", mask = TRUE) )
 ( r.ce <- raster.change(r1, r2, d = s, stat = "cross-entropy", mask = TRUE) )
 ( r.kl <- raster.change(r1, r2, d = s, stat = "divergence", mask = TRUE) )	
     
 opar <- par(no.readonly=TRUE)
 par(mfrow=c(3,2))
   plot(r.kappa, main="Kappa")
   plot(r.ttest[[1]], main="Paired t-test")
   plot(r.ent, main="Delta Entropy")
   plot(r.cor, main="Rank Correlation")
   plot(r.kl, main="Kullback-Leibler")
   plot(r.ce, main="cross-entropy")
 par(opar)

# }
# NOT RUN {
# }