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Both methods estimate target values from source values; they differ in the weight each assigns to a piece of a source polygon.
redistribute_direct assumes the
measure is spread uniformly by area within each source polygon.
It needs only the two polygon layers.redistribute_parcels assumes the
measure follows a point layer (e.g. parcels), which usually
tracks where people and housing actually are. It is more accurate where
such points exist, at the cost of needing that layer.library(sdc.redistribute)
data(sdc_example)
direct <- redistribute_direct(sdc_example$source, sdc_example$target,
extensive = "pop", suffix = "_direct")
parcels <- redistribute_parcels(sdc_example$source, sdc_example$target,
sdc_example$parcels, extensive = "pop",
suffix = "_parcels")
cbind(sf::st_drop_geometry(direct["pop_direct"]),
sf::st_drop_geometry(parcels["pop_parcels"]))
#> pop_direct pop_parcels
#> 1 90 90
#> 2 50 50
#> 3 60 60Both preserve the source total; they differ in how they place it.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.