The discrepancies caused by different cluster merging algorithms in fully polarimetric SAR classification are analyzed here. There are two often-used merging schemes, i.e., merging first to desirable cluster numbers and then iterative clustering and, the agglomerative hierarchical clustering, both using three different between-cluster distance measures herein. One sub-image of RadarSat-2 SAR SLC image is used here. The results illustrate that (1) The choice of between-cluster distance measures in merging scheme one affects the merging results obviously. (2) the agglomerative hierarchical clustering, the merging scheme two can significantly alleviate these discrepancies caused by different between-cluster distance measures and get almost the same merging results. (3) the agglomerative hierarchical clustering also will gain the stability of merging sequence when Pct is small enough.