lisa | R Documentation |
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.
lisa(x,d1,d2,statistic,...)
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.
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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