HIERARCHICAL CLASSIFICATION OF MAP UNITS USING THE SEAMLESS INTEGRATED GEOLOGIC MAPPING (SIGMA) EXTENSION TO THE GEOLOGIC MAP SCHEMA (GEMS) TO SUPPORT DYNAMIC ASSEMBLY AND REVISION OF LARGE GEOLOGIC MAP DATABASES (PART 2)

Geologic maps depict spatial geometry of physical geologic materials with measurable attributes that dictate logical groupings into distinct packages (map units). Within a local study area, we directly observe vertical, lateral, cross-cutting, and interfingering juxtaposition of these packages that define a framework between the units. This framework can be expanded by inferred correlations of similar, contemporaneous, or related materials and processes beyond the footprint of continuous outcrop. As the framework expands with new data, the complexity of interpretation expands creating a more conceptual classification scheme. The SIGMa extension to GeMS distinguishes the physical map unit from the conceptual framework to which it is assigned. Map units are placed into a variety of groupings that we call geologic provinces. We use a three-tier hierarchy to provide the user a national-scale (tier1), regional-scale (tier2), and local-scale (tier3) context for the map units. The local provinces (tier3) describe relationships between small groups of map units within a single depositional environment, basin, volcanic field, intrusive suite, or metamorphic assemblage. Regional provinces (tier2) define more interpretive correlations between spatially or temporally separated components of larger tectonic, magmatic, or depositional systems. These correlations are generally defined by data or models not restricted to simple outcrop or map relationships. At the highest level, continental-scale provinces (tier1) correlate large groupings of units with widely variable properties into broadly accepted, major systems that span long timeframes, across large parts of the continent. They are based upon genetic connection to uniform tectonic plate scale configurations such as subduction, rifting, or stable continental platforms. This relational hierarchy allows the user to easily access dense, large geologic map data for a wide range of analytical applications at variable scales while still maintaining the core, observational data that facilitates interoperation with external datasets created at local, regional, or continental scales. It also allows tremendous feature-level context when directly viewing and reading the map data.