How to do clustering on monthly collected data?

Question

I want to cluster 10 different sites based upon different parameters like temperature, humidity, rain, etc. for monthly data collected over a period of 2 years.

1. Should I use means of all 24 data samples for each parameter or the whole data sets?

2. Moreover, these parameters are on different scale of measurement: Is standardization necessary in this case? If so, how would I do it?

3. Finally, does there exist a cutoff value for deciding of clusters number in a dendrogram?

Answer 1

1. So you are undecided whether:

   • to cluster 240 points in 18 dimensional space or
   • cluster 10 points (means of 24 observations) in the same 18 dimensional space?

   I would go for clustering 240 points because clustering 10 points in such a high dimensional space has little sense. I guess your concern is that same site might end up in different clusters for different periods. If it is a problem in your case, you can assign each site to one cluster by most frequent cluster number, for example.

2. Standardization is a good way to make all dimensions comparable, so that when you compute distance between points you do not have dominant dimensions. There is also another option - to take 1-absolute correlation as a distance, then you do not need any standardization.

3. You could decide on the number of clusters or try to estimate it by various methods, using score function for example.