Coastal wetlands are structured by interacting environmental filters, including elevation, tidal inundation, salinity, and hydrological connectivity, which shape ecological communities along continuous gradients. Mangroves, saltmarshes, and supratidal forests therefore occur as mosaics of mixed vegetation states rather than sharply bounded units. Despite this, ecosystem mapping typically represents landscapes as discrete polygons, forming the basis of conservation planning, restoration evaluation, and ecosystem accounting. This representation obscures ecotones, ignores mixed communities, and constrains the sensitivity of monitoring frameworks, particularly where connectivity metrics rely on simplified habitat boundaries. Here, we develop and test a hybrid seascape mapping framework that integrates pixel-based classification with fixed-grid summarisation to represent coastal wetlands as continuous, proportional mosaics. Using high-resolution WorldView-2 imagery and ancillary geomorphic, hydrological, and structural predictors, we classified nine ecosystem and land-use classes across the Blue Heart coastal floodplain (Queensland, Australia). Outputs were aggregated to a 10 × 10 m grid to derive proportional ecosystem composition, seascape diversity, and spatial uncertainty. The framework captured fine-scale gradients and mixed assemblages while maintaining high classification accuracy, with uncertainty concentrated in ecotonal and restoration areas. In contrast to discrete polygon maps, this approach retains transitional habitats and spatial heterogeneity. Critically, it enables connectivity to be quantified across continuous gradients and proportional habitat mixtures rather than between simplified patches. This provides a scalable, policy-relevant framework for conservation planning, restoration monitoring, and ecosystem accounting in dynamic coastal systems.