Pycnophylactic Interpolation

Description

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.

Details

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.

Author(s)

Chris Brunsdon

Maintainer: Chris Brunsdon cb179@le.ac.uk

References

Tobler, W.R. (1979) Smooth Pycnophylactic Interpolation for Geographical Regions. Journal of the American Statistical Association, v74(367) pp. 519-530.

Examples

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# 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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