Description Usage Arguments Details Value Author(s) References Examples

Calculate local indicators of spatial association (LISA) for a continuous (numeric) variable at each location in a Raster layer or a SpatialPointsDataFrame or a SpatialPolygonsDataFrame.

1 |

`x` |
a raster object ( |

`d1` |
numeric lower bound of local distance (default=0), or an object of class neighbours created by dneigh when x is SpatialPoints or SpatialPolygons |

`d2` |
numeric upper bound of local distance, not needed if d1 is a neighbours object, |

`statistic` |
a character string specifying the LISA statistic that should be calculated. This can be one of "I" (or "localmoran" or "moran"), "c" (or "localgeary" or "geary"), "G" (or "localG"), "G*" (or "localG*") |

`...` |
additional arguments including |

This function can calculate different LISA statistics at each location in the input dataset. The statistics, implemented in this function, include local Moran's I ("I"), local Geary's c ("c"), local G and G* ("G" and "G*"). This function returns standardized value (Z) for Moran, G and G*.

`RasterLayer` |
if |

`Spatial*` |
if |

`numeric vector` |
if |

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. Anselin, L. 1995. Local indicators of spatial association, Geographical Analysis, 27, 93–115;

Getis, A. and Ord, J. K. 1996 Local spatial statistics: an overview. In P. Longley and M. Batty (eds) *Spatial analysis: modelling in a GIS environment* (Cambridge: Geoinformation International), 261–277.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
file <- system.file('external/dem_example.grd',package='elsa')
r <- raster(file)
plot(r,main='a continuous raster map')
mo <- lisa(r,d2=2000,statistic='i') # local moran's I (Z.Ii value)
plot(mo, main="local Moran's I (Z.Ii)")
mo <- lisa(r,d2=2000,statistic='i',mi='I') # local moran's I (Ii value (non-standardized))
plot(mo, main="local Moran's I (Ii))")
gc <- lisa(r,d2=2000,statistic='c') # local Geary's c
plot(gc, main="local Geary's c")
g <- lisa(r,d2=2000,statistic='g') # local G
plot(g, main="local G")
``` |

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