Sandeep,

I had a similar problem when I worked with wildlife GPS data and cluster
analysis, and I had over 50,000 points.

What I essentially did was... create a distance table for all points
(4500x4500 in your case)
Every row represents a spatial point and every column represents every other
point.  The elements are obviously the distance between points.  And of
course the diagonal elements are all zero (once you create the distance
table create a copy of it that you will edit).

Define a search radius (threshold) that will test every point from every
other point (basically processing the distance table you created).

If point A (row A) is within a distance d of point B (column B) then insert
a 'zero' in the matrix cell.  This is arbitrary but basically you edit the
copy of the distance table and only those points that have a nonzero entry
are the important points.  After you do that for the whole data set you have
a new distance table with numbers greater than zero and zero values.

I'll have to look through some old files to find the actual code but let me
know if you need more help.
-Roberto

On Sat, Oct 15, 2011 at 7:57 AM, Sandeep Patil
<sandeep.coepcivil@gmail.com>wrote:

> Hello all
>
> I have about 4500 spatial points which are irregularly spaced...
>
> What is want to do is to replace points that are clustered very near
>
> each other by one point ...i.e say the distance betweeen Point A & Point B
>
> is less than a threshold that i will define , i will delete either A or B
> and essentially
>
> do this for the complete dataset so that there is at least a minimum
> separation
>
> between every pair of points.
>
> Any idea how to proceed ?
>
> Sandeep
>
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>
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-- 
Roberto Fuentes Badilla
MS, Research Assistant
Wildlife Conservation and Management
School of Natural Resources and the Environment
University of Arizona

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