cross.tab

0th

Percentile

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, ...)
Arguments
x

rasterLayer class object

y

rasterLayer class object to compare to x

values

Expected values in both rasters

labs

Labels associated with values argument

pct

(TRUE/FALSE) return proportions rather than counts

...

Additional arguments

Value

a table with the cross tabulated counts

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)

# }
Documentation reproduced from package spatialEco, version 1.3-2, License: GPL-3

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