You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi Sébastien,
Probably not an issue and more of a "missuse", but hoping this is a good place to ask you about it:
I want to assign a df of Danish anglers (sea and inland waters) to their most probable municipality. So I thought of using regional_seas to add a coastal buffer around this municipality layer of Denmark, to try and catch the offshore anglers.
In the process, I lose a few of the municipalities, which seem to be the landlocked ones. Then, when I use the resulting layer to filter and assign the anglers, I'm missing many inland points.
Does the function "dissolve" the inland municipalities?
Hi Fernando,
I do not know if you finally succeeded in using this function.
I developed it for a single use, and never used it after that. So I am not sure the modifications of {sf} and other spatial packages did not change its behaviour.
You surely read the blog post already: https://statnmap.com/2020-07-31-buffer-area-for-nearest-neighbour/
Hi Sébastien,
Probably not an issue and more of a "missuse", but hoping this is a good place to ask you about it:
I want to assign a df of Danish anglers (sea and inland waters) to their most probable municipality. So I thought of using regional_seas to add a coastal buffer around this municipality layer of Denmark, to try and catch the offshore anglers.
In the process, I lose a few of the municipalities, which seem to be the landlocked ones. Then, when I use the resulting layer to filter and assign the anglers, I'm missing many inland points.
(Maybe this?
# Remove inside terrestrial parts
st_difference(x_union) %>%
st_cast()
)
The text was updated successfully, but these errors were encountered: