The Benthic Mapping Project of the Hudson River Estuary Program, which is funded by the New York State, has the goal to develop an improved understanding of the estuarine benthic habitats and sediment transport of the estuary. Presently over 100 km of the estuary floor have been surveyed with sidescan sonar, Chirp sub-bottom profiler, multi- and single-beam bathymetry. In addition, grab samples, coring and sediment profile imagery (SPI) have been taken to provide ground truth information. Analyzing and interpreting such amount of data is a labor-intensive task. Quantitative classification of the data set based on different parameter can aid the interpretation. Therefore, we have analyzed the possible use of different parameters as classifiers which include the variation in backscattered energy of the sidescan sonar as a function of grazing angle, reflection coefficient and relative reflection amplitude changes of the sub-bottom profiler at sea floor, and the insonification of the riverbed using different sidescan frequencies. The utility of each classifier as predictors of benthic habitats is investigated through the analysis of correlation between the classifiers and the sediment characteristics derived from grab samples, cores and SPI imagery. Some classifiers correlate more strongly with different sediment properties and our results indicate that some classifiers are more successful in some terrain than others. Furthermore, the use of different classifiers or a combination of them yields a more complete picture than the analyses of a single classifier.