The establishment of multibeam echosounders (MBES) as a mainstream tool in ocean mapping has facilitated integrative approaches toward nautical charting, benthic habitat mapping, and seafloor geotechnical surveys. The inherent bathymetric and backscatter information generated by MBES enables marine scientists to present highly accurate bathymetric data with a spatial resolution closely matching that of terrestrial mapping. Furthermore, developments in data collection and processing of MBES backscatter, combined with the quality of the co-registered depth information, have resulted in the increasing preferential use of multibeam technology over conventional sidescan sonar for the production of benthic habitat maps. A range of post-processing approaches can generate customized map products to meet multiple ocean management needs, thus extracting maximum value from a single survey data set. Based on recent studies over German Bank off SW Nova Scotia, Canada, we show how primary MBES bathymetric and backscatter data, along with supplementary data (i.e. in situ video and stills), were processed using a variety of methods to generate a series of maps. Methods conventionally used for classification of multi-spectral data were tested for classification of the MBES data set to produce a map summarizing broad bio-physical characteristics of the seafloor (i.e. a benthoscape map), which is of value for use in many aspects of marine spatial planning. A species-specific habitat map for the sea scallop Placopecten magellanicus was also generated from the MBES data by applying a Species Distribution Modeling (SDM) method to spatially predict habitat suitability, which offers tremendous promise for use in fisheries management. In addition, we explore the challenges of incorporating benthic community data into maps based on species information derived from a large number of seafloor photographs. Through the process of applying multiple methods to generate multiple maps for management applications, we demonstrate the efficient use of survey data sets to maximize the benefit to a wide number of potential end users, and to facilitate the move toward an ecosystem-based approach to management. (C) 2012 Elsevier B.V. All rights reserved.