Hi all,
it's my first time I write on this list.
I expose my problem quickly and (hope) clearly.

1) FIRST APPROACH:
I have some spatial points that are related to each other by some
spatial&temporal conditions. I have a dataframe that contains the couple of
points in relation. For example:

col1 ; col2
A       B
B       C
B       D
E       D

I've obtained this list of couples by creating some "dist" object and
searching correspondence between them.
This list of couples means that: A is relate to B, B is relate to C and to
D, E is relate to D.
I would like to write a script that create a vector in which I have: A B C D
E recognized as a unique group.
I've tried some "for loop" but I'm wondering if maybe there is a more
conventional function.

2) SECOND APPROACH:
In particularly I'm working on seismological data, and I'm studying a way to
recognize seismic sequences, so to elaborate space-time cluster on my data.
I have 2D spatial points with indication of time of occurrence of the seism,
and I would like to clusterize them with concern about these "3 dimensions":
coordinates x-y and time. I've successful used DBSCAN for space-clustering,
but it supports (I suppose) only 2 dimensions.

I give you at the end of the mail more details in case you would like to
help me.


Thanks very much for any help,
Riccardo


********************

My "3D" spatial-temporal points:

    utm_x  utm_y  date
1  100000 4200 <callto:000 4200>000 "2008-06-17 04:12:27 CEST"
2  155000 4250 <callto:000 4250>000 "2008-10-15 09:06:43 CEST"
3  277000 4750 <callto:000 4750>000 "2010-10-25 22:50:42 CEST"
...(5600 points)

My criterion to build cluster:
a- points within 3km of distance from each other
b- earthquakes happened within 14 days (2 weeks) from each other

	[[alternative HTML version deleted]]

