[R-sig-Geo] merge sliver polygons

[Murray Richardson]

Thanks Roger,

I have singletons with areas.  I think the slivers will be quite obvious 
based on their areas relative to the rest of the polygon areas.  I could 
even compute some perimeter to area index I supposed since they tend to 
be long a skinny.

So, my main uncertainty is still just how to work with the neighbour 
list to merge the sliver polygons with the LARGEST non-sliver polygon 
they share an edge with. i.e. to generate the new ids to use in 
unionSpatialPolygons.   I can't seem to find a good example of how to 
use the nb object in such a way.

cheers

Murray


Roger Bivand wrote:
> On Fri, 5 Sep 2008, Murray Richardson wrote:
>
>> Hi Roger
>>
>> I'm just getting around to trying this out. I must say, I'm not clear 
>> on how to work with the neighbour list object to accomplish this.  
>> Specifically, how would I identify the largest neighbours of the 
>> sliver candidates?
>>
>> Furthermore, do I first subset the polygons according to the area 
>> threshold, and then construct the neighbour list for only these 
>> candidate slivers?  I'm not clear on how to identify neighbours for a 
>> subset of polygons.
>
> My idea (IIRC!) was to look at a distribution of the areas of the 
> Polygon objects in the dataset. A good deal will depend on whether the 
> slivers are represented as separate Polygons objects (note the _s_), 
> or whether they are Polygon objects belonging to Polygons objects. So 
> nimbleness will be needed!
>
> library(maptools)
> xx <- readShapeSpatial(system.file("shapes/sids.shp", 
> package="maptools")[1],
>       IDvar="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
> pls <- slot(xx, "polygons")
> AREAS <- sapply(pls, function(x) sapply(slot(x, "Polygons"), function(y)
>       slot(y, "area")))
> summary(sapply(AREAS, length))
> summary(unlist(AREAS))
>
> is not a very good example, because the "areas" are planar in 
> non-planar coordinates, but I hope you see the point. If you have a 
> clear break in the distribution, you can find out which they are, and 
> where they are. If all the Polygons objects (the ones in the 
> "polygons" slot of your SpatialPolygons object, pls) are singletons, 
> things get much easier, because the merging will be between Polygons 
> objects, provided directly in maptools.
>
> This should be a start - once you have singleton Polygons objects with 
> areas as attributes, we can continue.
>
> Hope this helps,
>
> Roger
>
>>
>> Sorry to bother you with this again.  It will be very useful if it 
>> works as I would also like to use it for region merging based on 
>> other attributes.
>>
>> Still waiting on that book...!
>
> PS. Edzer, Virgilio and I did see the only copy in Europe in Dortmund 
> at useR! three weeks ago. It turns out that it was printed in the US, 
> and is at or awaited at the publisher's warehouse for dispatch. Things 
> seem to take time in the "real" world!
>
>>
>> Murray
>>
>>
>>
>> Roger Bivand wrote:
>>>  On Wed, 13 Aug 2008, Murray Richardson wrote:
>>>
>>> >  Hello again r.sig.geo list,
>>> > >  Thanks Roger, for help on my previous question regarding 
>>> iterating >  through a shapefile.
>>> > >  I'm sure once I receive my copy of  "Applied Spatial Data 
>>> Analysis with >  R" I will find answers to simple questions like 
>>> this on my own, but in >  the meantime....
>>> > >  Is it possible to merge sliver polygons that fall below a 
>>> certain >  threshold area with adjacent neighbours (e.g. perhaps 
>>> using >  unionSpatialPolygons but without aggregating any  
>>> polygons?).  If a >  sliver shares edges with more than one polygon, 
>>> it doesn't really matter >  which one it merges with, but if I had 
>>> to choose a rule I would have it >  merge with the largest one.
>>>
>>>  Not such a simple question ...
>>>
>>>  Both the Polygon and Polygons objects in the SpatialPolygons object 
>>> have
>>>  "area" slots, with different roles. The Polygon objects have a correct
>>>  naive area in the geometry of the coordinates taken as planar. The
>>>  Polygons objects use the "gross" area of Polygon objects belonging to
>>>  them, but "only" to provide the plot order (plot from largest to 
>>> smallest
>>>  to avoid over-painting).
>>>
>>>  If you "trust" the area slot of the Polygons objects (beware of hole
>>>  Polygon objects), you can first find your candidate slivers by 
>>> retrieving
>>>  the areas by:
>>>
>>>  Polygons_areas <- sapply(slot(SPobj, "polygons"),
>>>    function(x) slot(x, "area"))
>>>
>>>  and set a cutoff. Then use poly2nb(SPobj, queen=FALSE) in spdep to 
>>> find
>>>  the neighbours (rook criterion). Next use the output object to 
>>> identify
>>>  the largest neighbours of the sliver candidates, and build a "new
>>>  Polygons" ID vector. Finally, use unionSpatialPolygons(). I'm 
>>> assuming you
>>>  wouldn't have asked if there was useful data in the slivers!
>>>
>>>  Hope this helps,
>>>
>>>  Roger
>>>
>>> > >  Thanks in advance,
>>> > >  Murray Richardson
>>> >
>>>> _______________________________________________
>>> >  R-sig-Geo mailing list
>>> >  R-sig-Geo at stat.math.ethz.ch
>>> >  https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>> > >
>>
>