merge sliver polygons

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