`sf`

objectaggregate an `sf`

object, possibly union-ing geometries

```
# S3 method for sf
aggregate(
x,
by,
FUN,
...,
do_union = TRUE,
simplify = TRUE,
join = st_intersects
)
```

x

object of class sf

by

either a list of grouping vectors with length equal to `nrow(x)`

(see aggregate), or an object of class `sf`

or `sfc`

with geometries that are used to generate groupings, using the binary predicate specified by the argument `join`

FUN

function passed on to aggregate, in case `ids`

was specified and attributes need to be grouped

...

arguments passed on to `FUN`

do_union

logical; should grouped geometries be unioned using st_union? See details.

simplify

logical; see aggregate

join

logical spatial predicate function to use if `by`

is a simple features object or geometry; see st_join

an `sf`

object with aggregated attributes and geometries; additional grouping variables having the names of `names(ids)`

or are named `Group.i`

for `ids[[i]]`

; see aggregate.

In case `do_union`

is `FALSE`

, `aggregate`

will simply combine geometries using c.sfg. When polygons sharing a boundary are combined, this leads to geometries that are invalid; see https://github.com/r-spatial/sf/issues/681.

# NOT RUN { m1 = cbind(c(0, 0, 1, 0), c(0, 1, 1, 0)) m2 = cbind(c(0, 1, 1, 0), c(0, 0, 1, 0)) pol = st_sfc(st_polygon(list(m1)), st_polygon(list(m2))) set.seed(1985) d = data.frame(matrix(runif(15), ncol = 3)) p = st_as_sf(x = d, coords = 1:2) plot(pol) plot(p, add = TRUE) (p_ag1 = aggregate(p, pol, mean)) plot(p_ag1) # geometry same as pol # works when x overlaps multiple objects in 'by': p_buff = st_buffer(p, 0.2) plot(p_buff, add = TRUE) (p_ag2 = aggregate(p_buff, pol, mean)) # increased mean of second # with non-matching features m3 = cbind(c(0, 0, -0.1, 0), c(0, 0.1, 0.1, 0)) pol = st_sfc(st_polygon(list(m3)), st_polygon(list(m1)), st_polygon(list(m2))) (p_ag3 = aggregate(p, pol, mean)) plot(p_ag3) # In case we need to pass an argument to the join function: (p_ag4 = aggregate(p, pol, mean, join = function(x, y) st_is_within_distance(x, y, dist = 0.3))) # }