Seafloor Habitat Mapping on the Oregon Continental Margin: A Spatially Nested GIS Approach to Mapping Scale, Mapping Methods, and Accuracy Quantification

We implement a geographic information system (GIS) to map surficial geologic habitats (SGH) with varying scales at Nehalem Bank, Oregon, USA. Geologic interpretation was first used to produce a regional-scale SGH map of mega habitats. Local-scale algorithmic classification techniques were then implemented where data density and richness permitted the mapping of meso (10 m-1 km) macro scale (1-10 m) habitat features. We use a ranked-(data) density approach to assess the distribution and quality of input data for the regional SGH map. We then apply a virtual reference dataset and error matrix technique to assess the thematic accuracy of local-scale maps.