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.
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