this question started as "Clustering spatial data in R" and now has moved to DBSCAN question.
As the responses to the first question suggested I searched information about DBSCAN and read some docs about. New questions have arisen.
DBSCAN requires some parameters, one of them is "distance". As my data are three dimensional, longitude, latitude and temperature, which "distance" should I use? which dimension is related to that distance? I suposse it should be temperature. How do I find such minimum distance with R?
Another parameter is the minimum number of points neded to form a cluster. Is there any method to find that number? Unfortunately I haven't found.
Searching thorugh Google I could not find an R example for using dbscan in a dataset similar to mine, do you know any website with such kind of examples? So I can read and try to adapt to my case.
The last question is that my first R attempt with DBSCAN (without a proper answer to the prior questions) resulted in a memory problem. R says it can not allocate vector. I start with a 4 km spaced grid with 779191 points that ends in approximately 300000 rows x 3 columns (latitude, longitude and temperature) when removing not valid SST points. Any hint to address this memory problem. Does it depend on my computer or in DBSCAN itself?
Thanks for the patience to read a long and probably boring message and for your help.