Compute sample (empirical) variogram from spatial data. The function returns a binned variogram and a variogram cloud.
Usage
Variogram(x, width, cutoff,...)
Arguments
x
a spatial object (RasterLayer or SpatialPointsDataFrame or SpatialPolygonsDataFrame)
width
the lag size (width of subsequent distance intervals) into which cell pairs are grouped for semivariance estimates. If missing, the cell size (raster resolution) is assigned.
cutoff
spatial separation distance up to which cell pairs are included in semivariance estimates; as a default, the length of the diagonal of the box spanning the data is divided by three.
...
Additional arguments including cloud that specifies whether a variogram cloud should be included to the output (default is FALSE), zcol (when x is Spatial* object, specifies the name of the variable in the dataset; longlat (when x is Spatial* object, spacifies whether the dataset has a geographic coordinate system; s (only when x is a Raster object, it would be useful when the dataset is big, so then by specifying s, the calculation would be based on a sample with size s drawn from the dataset, default is NULL means all cells should be contributed in the calculations)
Value
Variogram
an object containing variogram cloud and the variogram within each distance interval
Details
Variogram is a graph to explore spatial structure in a single variable. A variogram summarizes the spatial relations in the data, and can be used to understand within what range (distance) the data is spatially autocorrelated.
References
Naimi, B., Hamm, N. A., Groen, T. A., Skidmore, A. K., Toxopeus, A. G., & Alibakhshi, S. (2019). ELSA: Entropy-based local indicator of spatial association. Spatial statistics, 29, 66-88.
# NOT RUN {file <- system.file('external/dem_example.grd',package='elsa')
r <- raster(file)
plot(r,main='a continuous raster map')
en <- Variogram(r, width=2000)
plot(en)
# }# NOT RUN {# }