[postgis-users] 'Clustering' records in space and time

Pierre Racine Pierre.Racine at sbf.ulaval.ca
Thu Jul 15 13:33:18 PDT 2010


I would suggest you ask your question to the r-sig-geo mailing list. You will get a R solution. You can then get your PostGIS table from R using the gdal/ogr package or use PL/R in PostgreSQL.

Pierre

>-----Original Message-----
>From: Dylan Beaudette [mailto:debeaudette at ucdavis.edu]
>Sent: 15 juillet 2010 16:02
>To: Pierre Racine
>Cc: PostGIS Users Discussion; will at thearete.co.uk
>Subject: Re: [postgis-users] 'Clustering' records in space and time
>
>On Thursday 15 July 2010, Pierre Racine wrote:
>> What should happen when event A is at a distance n minus epsilon from B, B
>> is at a distance n-epsilon from C but A is at a distance 2*n-epsilon from
>> C? Should A and C be in the same cluster with B?
>>
>> Pierre
>
>Interesting. The choice of clustering algorithm would need to be based on the
>questions the OP was trying to answer. Without much thought (warning!) I
>pictured a 3D space (x, y, time) partitioned around medoids (PAM algorithm)
>of data.
>
>In this very simple case chunks of data in (x, y, time) space would be
>collected based on their proximity. For this to work, space and time
>coordinates would need to be standardized accordingly... For x and y, I think
>that subtracting the mean and dividing by the standard deviation should do. I
>am not sure about the standardization of time... maybe the same thing, but
>applied to the number of seconds | minutes | hours | days elapsed since the
>start of the experiment?
>
>Dylan
>
>
>> >-----Original Message-----
>> >From: postgis-users-bounces at postgis.refractions.net [mailto:postgis-users-
>> >bounces at postgis.refractions.net] On Behalf Of Dylan Beaudette
>> >Sent: 15 juillet 2010 15:10
>> >To: will at thearete.co.uk; PostGIS Users Discussion
>> >Subject: Re: [postgis-users] 'Clustering' records in space and time
>> >
>> >Hi,
>> >
>> >Can you give us some hints about your data?
>> >
>> >1. how many records
>> >2. temporal domain (i.e. 1 year?)
>> >3. spatial domain (local, regional, continental?)
>> >
>> >If you don't have too much data, you may be able to standardize them, and
>> >apply an algorithm like PAM, or CLARA (see cluster package in R).
>> >
>> >Cheers,
>> >Dylan
>> >
>> >On Thursday 15 July 2010, William Furnass wrote:
>> >> I have a PostGIS table of records describing events therefore the
>> >> table has a timestamp attribute.  I wish to replace 'clusters' of
>> >> events that occur within a m-hour window and a spatial radius of n
>> >> with single events which have the mean timestamp and central position
>> >> of the cluster.  I understand that I can quantize my data spatially
>> >> using the St_SnapToGrid function but using this function alone I lose
>> >> some of the distinct events that occurred at the same point in space
>> >> but at very different times (it's my understanding that St_SnapToGrid
>> >> only allows one point to be stored at each node in the grid).  Also, I
>> >> am unsure as to how I could use St_SnapToGrid in such a way so as not
>> >> to relocate points that are unique within the aforementioned spatial
>> >> and temporal window boundaries.
>> >>
>> >> Has anyone any suggestions as to how this can be achieved
>> >> programmatically using SQL (rather than a graphical tool)?  Should I
>> >> perhaps be looking to use R to spatially and temporally cluster my
>> >> data?  Apologies if the description of my problem isn't particularly
>> >> clear; it's been a long day:)
>> >> _______________________________________________
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>> >
>> >--
>> >Dylan Beaudette
>> >Soil Resource Laboratory
>> >http://casoilresource.lawr.ucdavis.edu/
>> >University of California at Davis
>> >530.754.7341
>> >_______________________________________________
>> >postgis-users mailing list
>> >postgis-users at postgis.refractions.net
>> >http://postgis.refractions.net/mailman/listinfo/postgis-users
>
>
>
>--
>Dylan Beaudette
>Soil Resource Laboratory
>http://casoilresource.lawr.ucdavis.edu/
>University of California at Davis
>530.754.7341



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