data(land)
landb <- brick(land)
lb <- aggregate_map(land, fact=2)
qtm(lb, raster="trees")
lb2 <- aggregate_map(landb, fact=2)
qtm(lb2, raster="cover_cls")
lb3 <- aggregate_map(land, fact=2, agg.fun = list(cover=modal, trees=function(i, na.rm) sample(i, size = 1)))
qtm(lb3, raster="cover")
qtm(lb3, raster="trees")
lb4 <- aggregate_map(landb, fact=16, agg.fun = "last")
qtm(lb4, raster="cover")
qtm(lb4, raster="trees")
landr <- raster(land, 3)
lr <- aggregate_map(landr, fact=16, agg.fun = "modal", na.rm=T)
qtm(lr)
data(NLD_muni)
NLD_prov2 <- aggregate_map(NLD_muni, by="province")
NLD_prov2 <- aggregate_map(NLD_muni, by="province", weights = "AREA")
NLD_prov2 <- aggregate_map(NLD_muni, by="province", agg.fun = list(population="sum", origin_non_west="mean", name="modal"), weights = "population")
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