Efforts to develop a procedurally robust method for automated classification of multibeam backscatter have taken a variety of approaches (e.g., image-based, textural, angular range analysis). For image-based classification, little research has focused on the roles of operational parameters of vessel and sonar system in affecting the final classification. Repeat multibeam surveys (2005 and 2006) conducted at the same area with different sounding densities were classified using QTC-Multiview. Comparison of class areas revealed 78% agreement between classifications derived from the two surveys. Cross-tabulation of ground truth video and class demonstrate 71% agreement in the low-density survey and 77% for the high-density. Differences between classifications are primarily attributed to variation in along track data density, errors in the compensation process, and/ or insufficient quality control of the input data. Natural change detection at the scales observed was determined not to be practically discernable from the errors associated with the classification process.