[R-sig-Geo] Calculate shortest distance between points belonging to different polygons

[Adrian Baddeley]

After you do 
    > nn.within.pol<-nndist(randp.df[,c(2,3)], by=factor(randp.df$Polygon_ID))

the result nn.within.pol is a matrix with one row for each data point, and
one column for each polygon. The entry on row i, column j is the distance 
from the i-th data point to its nearest neighbour in polygon j.

It's still not clear to me what you wanted to calculate.

Do you want the minimum distance between any two points in different polygons?
For each possible pair of polygons? or... ?

The command 
      
     >   aggregate(nn.within.pol, by=list(from=factor(randp.df$PolygonID)), min)

would yield a matrix, with one row and column for each polygon,
in which the [i,j] entry is the minimum distance between any point in polygon i
and any point in polygon j. On the diagonal the [i,i] entry would give the minimum
nearest-neighbour distance for the pattern of points within polygon i.


Prof Adrian Baddeley FAA
Curtin University
________________________________________
From: Ivan Palmegiani [pan.sapiens.it at gmail.com]
Sent: Wednesday, 18 February 2015 12:32 PM
To: Adrian Baddeley
Cc: r-sig-geo at r-project.org
Subject: Re: [R-sig-Geo] Calculate shortest distance between points belonging to different polygons

Dear Adrian,

Thank you very much!

I made the change you suggested and the outcome is not exactly the one I wanted...but it's very close to it!

> library(spatstat)
> nn.within.pol<-nndist(randp.df[,c(2,3)], by=factor(randp.df$Polygon_ID))
> nn.within.pol

                           1                   2                 3                     4                     5                   6                     7                     8                   9                   10              11                    12              13
  [1,]  77758.488  71978.036 33715.961  62236.2421  84528.6758 47206.9703 26370.4913  39448.7910  40198.916  68559.0147  67769.69 39298.45411  2579.422
  [2,]  63404.130  93535.612 64780.940  21597.4530  32485.1889  1391.8891 38473.2915  69642.7457  24374.408  15070.9926  70237.22 35217.62792 49217.807
  [3,]  37861.018  53839.721 27587.333  59658.5379  58107.6351 35133.6718 48282.9013  75710.3428  48898.652  52273.7298  33882.71    59.85628 36756.945
  ...
 [98,] 114435.572 111577.598 73735.852  65518.7127 102369.5236 65629.7084 29330.3308    955.2648  39271.208  81234.4457 107270.98 74005.63912 30371.918
 [99,]  32283.616  52705.045 28666.796  61665.1649  55854.9164 36094.8633 53239.2478  81208.2781  52669.590  52158.4953  30242.29  3166.00894 42467.270
[100,]  38187.593  53418.183 27001.456  60050.0374  58795.8736 35555.5710 48200.6059  75445.7086  49047.448  52858.1932  33791.42   705.25663 36323.229

In fact, I realized that I do not need to make recourse to aggregate() because in the matrix above I already have the information I need. I just need to extract it.
Is there any way to prevent the function to calculate the distance between a point and its nn within the same group (i.e. distance [1, 13]; [2, 6]; [3, 12]; etc.)?

If not, I will just extract the second shortest distance per point (the shortest one is certainly within the same group) and I will get exactly the information I need.

Thanks again!

Sincerely,

Ivan


On 17-Feb-15 16:01, Adrian Baddeley wrote:

Ivan Palmegiani <pan.sapiens.it at gmail.com><mailto:pan.sapiens.it at gmail.com> writes:



I'm handling a SpatialPointsDataFrame with 100 ramdom points distributed
within 13 different polygons.



 > randp


                     coordinates   Point_ID   Polygon_ ID
0  (690926.8, 7522595)         1_hs                    13
1  (696727.1, 7576122)         2_hs                      6





I need to calculate the shortest distance between points belonging to
different polygons. Basically I'd like to do what nndist {spatstat} does.
The difference is that the distance should be calculated between
groups of points instead of within a group of points.



              Well, nndist {spatstat} does that too.



I tried to use "aggregate" as suggested below but it didn't work out for me.
http://www.inside-r.org/packages/cran/spatstat/docs/nndist





Please find my try below:





 > randp.df<-data.frame(randp)
 > randp.hs.df
        Point_ID     coords.x1      coords.x2   Polygon_ ID
0            1_hs     690926.8       7522595 13
1            2_hs     696727.1       7576122 6
2            3_hs     723480.7       7546594 12





library(spatstat)





# Calculate nearest neighbors within a polygon
 > nn.within.pol<-nndist(randp.df[,c(2,3)],by=marks(randp.df$Polygon_ID))



              'marks' is not appropriate here.
              marks() is a function that extracts the marks from a marked point pattern (class 'ppp')
              but you are applying it to a numeric vector. The result is NULL.

              The argument 'by' should be a factor that determines the grouping.

              Just change 'marks' to 'factor' so that the numeric polygon ID will be treated as a factor,

 nn.within.pol<-nndist(randp.df[,c(2,3)],by=factor(randp.df$Polygon_ID))

               and proceed as before (also changing the other instances of 'marks' to 'factor')



Adrian Baddeley
spatstat author