# correlogram: Correlogram of Spatial Data In babaknaimi/elsa: Entropy-Based Local Indicator of Spatial Association

 correlogram R Documentation

## Correlogram of Spatial Data

### Description

Compute Correlogram of spatial data. The function returns a binned correlogram by calculating Moran's I (spatial autocorrelation) in different range of distances.

### Usage

```correlogram(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 `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)

### Details

Correlogram is a graph to explore spatial structure in a single variable. A correlogram summarizes the spatial relations in the data, and can be used to understand within what range (distance) the data is spatially autocorrelated.

### Value

 `Correlogram` an object containing Moran's I values within each distance interval

### Author(s)

Babak Naimi naimi.b@gmail.com

### 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.

### Examples

```
file <- system.file('external/dem_example.grd',package='elsa')
r <- raster(file)
plot(r,main='a continuous raster map')

co <- correlogram(r, width=2000,cutoff=30000)

plot(co)

```

babaknaimi/elsa documentation built on Nov. 21, 2022, 12:33 a.m.