Classification Listserve Members, I am working on a clustering method that can be applied to digital river networks in a geographic information system. Essentially, the goal is to cluster adjoining river reaches (i.e., river reaches that flow into each other) into larger habitat units (i.e. patches, valley segments) based on habitat data that are attributed to each river reach. I have found that most standard clustering methods do not work well with this type of data because the methods do not recognize the fact that only adjoining reaches should be clustered. I thus have constructed an algorithmn that will "crawl" through a river network and form patches one at time by iteratively merging adjoining river reaches, until no more adjoining reaches satisfy the merging threshold. Once a patch is formed, all reaches that comprise that patch are dropped from the candidate list of reaches so that they will not get clustered into another habitat patch. Right now, I am basing my threshold value on the average (or some other statistic) of the pairwise Euclidean differences between all river reaches in the network. Clustering also is based on Euclidean differences in the habitat variables. The method seems to work fairly well, but I would now like to try and merge neighboring patches into larger units until some "optimum" level of patches is found (although I realize "optimum" is probably a myth). Essentially, this concerns the implementation of a stopping rule for forming clusters. My current stopping rule is based on the Calinski and Harabasz (1974) index, which in a nutshell is the ratio of the between and pooled within cluster sum of squares. I thus iteratively merge the most similar patches until the Calinski and Harabasz index can no longer be improved. My question is whether the Calinski and Harabasz index is useful for this type of application (trying to find an "optimum" number of clusters) or to see if anybody had any other suggestions as to a better stopping rule? I would also be interested to hear if anybody had other suggestions concerning how to cluster only adjoining river reaches. I have done a number of web searches for a better method but I have always come up empty. To me, this is a form of spatially-constrained clustering, but I have not come across anything similar in other fields. Thanks in advance for any suggestions that might be provided. Travis -- Travis Brenden School of Natural Resources and Environment University of Michigan 212 Museums Annex Ann Arbor, MI 48109-1084 734-663-3554 (Ext. 122) [log in to unmask]