I am trying to remove spatial 'duplicates' from a point dataset. The
coordinates won't be exactly the same and so I can't use the normal methods for
removing the second instance of the points. This generalizes to a question
about removing points nearby others, either randomly or based on other criteria
(in my case, I want to keep the one with a more recent date attribute).
Although my research and fiddling has got me close, I wonder if there already
is a solution I'm missing within the various spatial packages so I'm starting
with sig-geo, even though I'm stuck at a spot that would use regular R syntax.
My approach (code at bottom of email):
1. Move the full point data set over to SpatialPoints as decimal degrees
longlat [package=sp]
2. Reproject to utm, using spTransform
3. convert to ppp
4. find the distance from each point to its nearest using nndist() [package =
spatstat]
5. identify that nearest using nnwhich() [package = spatstat]
6. extract those with neighbors closer than 100m
** this is where I'm stuck ** I now have a list of neighbors, for which I'd
like to keep the first case of each neighbor but remove the second (and
sometimes third). Similar to unique(). Here's a dummy example
#set up dummy data frame, the dist and neigh columns are from nndist() and
nnwhich(), respectively
a <-
data.frame(ID=c("one","two","three","four"),dist=c(2.2,5.1,5.1,2.2),neigh=c(4,3,2,1))
#here's as far as I've got, I can remove the neighbor to row one with the
following line.
#a looping solution seems problematic as the size of the dataframe changes with
each loop
b <- a[-match(a$neigh[1], rownames(a)),]
Questions:
- Is there already a function in a spatial package that offers a way to remove
points within a certain distance of others?
- if not, does anyone have any hints for taking the next step from what I've
done?
### code for what I've got so far.
### dat.wind.tall is the input DF of lat long decimal degree coordinates
library(sp)
library(spatstat)
library(maptools)
library(rgdal)
llCRS <- CRS("+proj=longlat +datum=NAD83")
wind.sp <- SpatialPoints(dat.wind.tall[,c(66,65)], proj4string=llCRS)
prjNew <- CRS("+proj=utm +zone=18 +datum=NAD83")
wind.utm <- spTransform(wind.sp, prjNew)
wind.ppp <- as(as(wind.utm, "SpatialPoints"), "ppp")
turb.dist <- nndist(wind.ppp)
turb.nearest <- nnwhich(wind.ppp)
dat.wind.tall.nbr <- cbind(dat.wind.tall, nneigh=turb.nearest, dist=turb.dist)
closeNeighbors <- dat.wind.tall.nbr[turb.dist<100,]
#code for removing neighbor to first row.
y <- closeNeighbors[-match(closeNeighbors$nneigh[1], rownames(closeNeighbors)),]
Thanks in advance for any help.
Tim
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