Description Usage Arguments Details Value Author(s) References Examples

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

1 | ```
correlogram(x, width, cutoff,...)
``` |

`x` |
a spatial object ( |

`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 |

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.

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

Babak Naimi naimi.b@gmail.com

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.

1 2 3 4 5 6 7 | ```
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)
``` |

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