Cluster analysis classifies a system of variables into clusters on the basis of similarities (or dissimilarities) such that each cluster represents a specific process in the system [2, 36]. Some studies showed that a classification scheme for ecological data using the Euclidean distance for similarity measures and Ward’s method for linkage generates effective results
In this study, the hierarchical cluster analysis (HCA) using Euclidean distance for similarity measures and Ward’s method for linkage was applied to the raw data for the entire indicators list in Table 2 to classify the data to several groups. The statistic software of SPSS 13. 0 was used in HCA. Ecological restoration goals were determined according to the results of the cluster analysis.