R – Calculate Distance Between Points and Nearest Polygon

distancer

I have a data frame with among others longitude and latitude as variables for about 17,000 points. I also have a shapefile consisting of multiple polygons. The points fall inside or outside the polygons. I would like to add to the data frame the distance to nearest polygon for each point but i have been struggling quite a lot.

This is what i have so far after reading multiple posts on the topic but this only works for points inside the polygons apparently.

library(spatstat)
library(maptools)
shp_Poly <- readShapeSpatial("POLYGON.shp")
W <- as.owin(shp_Poly_BAT)
W <- as.psp(W)
p <- ppp(lon, lat, W)
AVG <- nncross(p, W)

How can i improve this?

Best Answer

Let's set up some sample data:

library(sp)
library(spdep)
example(columbus)
plot(columbus)

We'll now get some points. Click 20 times on the map, some inside and some outside polygons:

pts = locator(20,type="p")

Convert to Spatial data type:

spts = SpatialPoints(pts)

Now use rgeos to compute point-polygon distances, and take the minimum for each point:

library(rgeos)
> apply(gDistance(spts, columbus,byid=TRUE),2,min)
         1          2          3          4          5          6          7 
0.25947439 0.03898401 1.27156515 1.50490316 0.00000000 0.00000000 0.00000000 
         8          9         10         11         12         13         14 
0.00000000 0.00000000 0.31312329 0.26742466 0.53934325 0.07764322 0.03909773 
        15         16         17         18         19         20 
0.11156343 0.29243322 0.08872334 0.00000000 0.00000000 0.00000000

There you go. That's the minimum distance from each of the 20 points to any of the polygons. The zeroes are for points inside one of the polygons.

Note you should use data in a projected spatial coordinate system and not lat-long.

If you have 17,000 points then you might want to do this in smaller subsets to avoid creating a 17,000 x 5,000 matrix if you have 5,000 polygons. You didn't say.

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