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.