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I believe the general outline (partly tested so far) is: Find the points representing stream sources, as in this answer. Intersect with the polygons table to get a count of source vertices by polygon. Use ST_DumpPoints in conjunction with group by geometry to get a count of each point. The idea being to get a count of how many rivers meet at a given point. ...
This is how I'd do it with PyQGIS: In your QGIS ToC, turn off those layers that you want to keep untouched, i.e., leave visible only the layers you want to set the filter to. Now open a QGIS Python console and paste this code: layers = iface.mapCanvas().layers() for layer in layers: layer.setSubsetString('"osm_user" = \'donlaser\'') This should do ...
Okay, I found out why the lat lng data was that strange in this case. For importing the data with osm2pgsql in slime node the additional table named planet_osm_nodes is getting generated and that was the one I used. Without the additional parameter -l in the import statement the coordinates are getting projected in the Sperical Mercator projection EPSG:3857. ...
You could use ST_LineMerge http://postgis.net/docs/ST_LineMerge.html First you need join all your ways into one MultiLineString using ST_DUMP http://postgis.net/docs/ST_Dump.html and ST_Multy Afterwards use ST_LineMerge to get a set of Linestrings of maximum length sewed from segments.
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