Citizen science observations represent a significant and growing source of species and ecosystem knowledge. These data have potential to support traditional surveys. Databases of citizen observations of wildlife are growing, but how to use this information for scientific purposes is less clear owing to uncertainty in sampling distribution and data quality. In this study, we demonstrate how mapping cetacean patterns using citizen observations and systematic surveys generate consistent and different understandings of cetacean distributions and densities, and evaluate potential risk by assessing cumulative human effects in British Columbia, Canada. We used GIS-based map comparison methods that quantified differences and similarities between geographic datasets to locate where cetacean distributions and densities had spatially unique or spatially analogous representation. Where spatial clusters in both data sources are congruent, we interpret with a higher level of confidence that species occur, and mapped patterns accurately reflect distribution and density. In areas where datasets exhibit dissimilar species densities and distributions, we acknowledge lower confidence and advise further sampling. Regions of agreement were primarily in the central-western portion of the study area (off the southeastern coast of Haida Gwaii); areas of disagreement were heterogeneously distributed across the study area. Spatial clusters from citizen data exhibited significantly higher cumulative human effect scores than from systematic surveys, despite previous data adjustments for human effort. We demonstrate the use of citizen observations as a confirmatory dataset to broaden ecological exploration by augmenting scientific survey datasets and identifying strategic areas for future data collection efforts.