SEAMLESS, INTEGRATED DIGITAL GEOLOGIC MAP FOR THE INTERMOUNTAIN WEST

Geologic maps are critical elements for understanding Earth’s evolution. Geologic processes responsible for the global distribution of earth materials are interpreted and modeled based largely on geologic map, geophysical, geochemical, and geochronologic data. Derivative geologic framework models are vital for management of mineral, water, and energy resources, environmental health, hazards, and ecosystems. While traditional geologic maps contain this critical information, they are not easily integrated with associated digital data sets or across map boundaries at regional scales applicable for modeling tectonic processes and constraining groundwater, mineral and energy assessments, and systems modeling.

The USGS Geologic Framework of the Intermountain West project has created an extension for the geologic map schema (SIGMa-GeMS), a workflow, and a data delivery system that aims to facilitate the integration of and improve access to geologic data at regional scales. This effort derives from the National Cooperative Geologic Mapping Program’s goal to develop seamless, integrated digital geologic map data for the Nation. This innovative approach to integrating geologic information synthesizes new and existing geologic mapping into consistent framework models of surficial and bedrock geology. Source metadata and the improved ability to query feature level attribution allows these data to be viewed as thematic layers, which act as examples for users to build their own derivative products. The stratigraphic framework that underpins the geologic mapping is constructed dynamically using a process-based, time-dependent hierarchical classification of map units. This dataset can be integrated with users’ data via GIS hosted feature layers or can be viewed using the Intermountain West Geologic Map Explorer, an ESRI hosted web app that will be updated with new map publications as they are released. This approach to geologic mapping will serve as the foundational dataset for future research projects and assessments of natural and economic resources.