3

I have vectorized raster as in the image. This is actually 1419 polygons in SpatialPolygons class object.

example1

I'm looking for a method which would allow me to extract the one most external polygon (boundary shape). I've found concave method which works for 95% of cases but not in this particular one. As follows the code:

sfn <- sf::st_as_sf(the_polygon)
sfu = sf::st_union(sfn)
gpts = sf::st_coordinates(sfu)
gmat <- matrix(c(gpts[,1], gpts[,2]), ncol = 2)

I can adjust parameters:

cm = concaveman::concaveman(gmat, 0.5, 1)
chp = SpatialPolygons(list(Polygons(list(Polygon(cm)), ID=n)))

this gives such vector: example2 but choosing the first parameter as 0.1 takes: example3

So there's no optimal shape, I've tested values between those 2 and further as well. The second parameter doesn't make much - it just smoothes the lines.

I'd like to ask from your experience what kind of approach I'd take? For example, if I had a function which fills the outside area, then selects "negative" and makes borderline and that border would be good approximate of what I need. Notice it's a vector(s). Have anyone some idea? In terms of fill the vectors area what libraries I'd choose?

EDIT

Incredible things happen: I've fit this almost ideally using concaveman(gmat, 0.01, 2.2) - just tested with "bruteforce plot". So, in this case, answer been partially found.

1

You can try the chull function, which calculates the convex hull of the coordinates of your polygon(s). Try

cv.id <- chull(gmat)
cv.id <- c(cv.id, cv.id[1])
plot(gmat, cex = 0)
lines(gmat[cv.id, ])
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