cross.tab

Class comparison between two nominal rasters

Compares two categorical rasters using Cohen's Kappa (d) or paired t-test statistic(s)

Usage

cross.tab(x, y, values = NULL, labs = NULL, pct = FALSE, ...)

Note

This function returns a cross tabulation between two nominal rasters. Arguments allow for labeling the results and returning proportions rather than counts. It also accounts for asymmetrical classes between the two rasters

References

Pontius Jr, R.G., Shusas, E., McEachern, M. (2004). Detecting important categorical land changes while accounting for persistence. Agriculture, Ecosystems & Environment 101(2):251-268.

See Also

raster::crosstab

Aliases

• cross.tab

Examples

# NOT RUN {
 library(sp)
 library(raster)
   data(meuse.grid)
 
 r1 <- sp::SpatialPixelsDataFrame(points = meuse.grid[c("x", "y")], 
                                  data = meuse.grid)
 lulc2010 <- raster(r1)
   na.idx <- which(!is.na(lulc2010[]))
     lulc2010[na.idx] <- sample(1:5, length(na.idx), replace=TRUE)
  
 lulc2020 <- raster(lulc2010)
   lulc2020[na.idx] <- sample(1:5, length(na.idx), replace=TRUE)
 
 ( v = sort(unique(c(lulc2010[], lulc2020[]))) )
 l = c("water","urban","forest",
       "ag","barren")

 cross.tab(lulc2010, lulc2020) 
 cross.tab(lulc2010, lulc2020, values = v, labs = l)
 cross.tab(lulc2010, lulc2020, values = v, labs = l, pct=TRUE)

# Create asymmetrical classes 
lulc2020[na.idx] <- sample(c(1,2,4,5), length(na.idx), replace=TRUE)

cross.tab(lulc2010, lulc2020, values = v, labs = l, pct=TRUE)

# }