Description Details Author(s) References Examples
Given a SpatialPolygonsDataFrame and a set of populations for each polygon, compute a population density estimate based on Tobler's pycnophylactic interpolation algorithm. The result is a SpatialGridDataFrame.
Package: | pycno |
Type: | Package |
Version: | 1.0 |
Date: | 2011-04-15 |
License: | GPL (>=2) |
LazyLoad: | yes |
For use in conjunction with the sp package, computes pycnophylactic surfaces given a SpatialPolygonsDataFrame and a population for each poplygon. A pycnophylactic surface is smooth, but populations allocated to each pixel sum up to the initial polygon counts, when summed over the polygons contained in each pixel.
Chris Brunsdon
Maintainer: Chris Brunsdon cb179@le.ac.uk
Tobler, W.R. (1979) Smooth Pycnophylactic Interpolation for Geographical Regions. Journal of the American Statistical Association, v74(367) pp. 519-530.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # Read in data for North Carolina as a SpatialPolygonsDataFrame
nc.sids <- readShapeSpatial(system.file("shapes/sids.shp", package="maptools")[1],
IDvar="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
# Compute the pycnophylactic surface for 1974 births as a SpatialGridDataFrame
# Note probably shouldn't really base grid cells on Lat/Long coordinates
# This example just serves to illustrate the use of the function
births74 <- pycno(nc.sids,nc.sids$BIR74,0.05, converge=1)
# Draw it
image(births74)
# Overlay North Carolina county boundaries for reference
plot(nc.sids,add=TRUE)
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