tomasstraupis at gmail.com
Mon Apr 16 17:23:14 UTC 2018
2018-04-16 19:34 GMT+03:00 Marco Boeringa wrote:
> No, buildings are not the most interesting. I once generalized all buildings
> in Denmark. It only reduced the storage by maybe 5%, at the high cost of
> heavily distorting a large number of them. Most buildings in OSM are in fact
> already in their most generalized state: just 4 nodes. Unless you think
> triangles is a suitable representation ;-)
Interesting, what algorithm did you use?
I'm playing around in Vilnius which has urban houses, big block
houses, industrial zones and old town with lots of connected buildings
of very irregular shapes.
In Vilnius there are 54267 buildings tagged with 366979 vertexes.
Clustering them with distance of 5m gets 45810 objects (of course
with the same number of vertexes).
Removing buildings with area < 100 and having neighbours in < 500
meters I'm left with 28974 buildings with 299224 vertexes.
Simplification (amalgamating buildings in the cluster and trying to
remove edges < 20m) reduces the number of vertexes to 117108.
So this is much more than 5%.
There are still a lot of problems (no triangles:), but I do not
expect number of vertexes to rise considerably.
Even "dumb" generalisation (st_buffer+- with join=mitter) reduces
vertex count by ~25%.
Reducing storage/tile size is not the only/main purpose of generalisation.
> Besides, buildings are only shown at high zoom,
> while generalization is most needed and beneficial at
> low zoom. Lastly, most vector generalization algorithms are primarily
> designed and effective for rather smooth and node rich data, like a
> stream-digitized feature, neither of which relates to square buildings.
> Hence i consider generalizing buildings largely senseless.
I suspect you're talking about st_simplify(preservetopology) use in
vector tile generators. Which as mentioned earlier is only technically
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