T30 Geology across Geographic Boundaries: Identifying Challenges and Opportunities Related to the Creation of a Digital Geologic Map of the United States by the End of This Decade (Posters)

Sunday, 9 October 2022
9:00 AM - 1:00 PM
Exhibit Hall F

VISUALIZING UNCERTAINTY IN DIGITAL GEOLOGIC MAP DATABASES

Paper number: T30-16
Program: Technical Sessions
Time: 9:00 AM – 1:00 PM

Authors

  • Kathleen Warrell
    University Corporation For Atmospheric Research, Boulder, CO
  • Amy Gilmer Presenting Author
    Geosciences and Environmental Change Science Center, Denver, CO
  • Kenzie Turner
    Geosciences and Environmental Change Science Center, Denver, CO
  • Ren Thompson
    Geosciences and Environmental Change Science Center, Denver, CO

Abstract

The geologic map remains the primary tool geologists use to model and communicate what we know about Earth’s surface. All geologic models contain some level of uncertainty, but this uncertainty is rarely incorporated in traditional geologic maps, potentially limiting application by decision makers. Even as our geological depictions have migrated to digital geologic map databases, our map symbology has largely remained the same as that used on traditional paper maps. While varying dash length for contacts and faults may convey a relative sense of uncertainty to experienced users, it does not convey meaning to the nonexpert user. Cartographic uncertainty visualizations are an effective way to communicate how well we know what and where something is.

The adoption of the Geologic Map Schema (GeMS) standard for geologic maps has enabled geologists to capture feature-level metadata, including location uncertainty, as well as feature identity and existence confidence. To visually communicate the underlying locational uncertainty in the USGS Intermountain West geological framework database, we have developed an ArcGIS Python toolbox that extracts existing location confidence data from feature attributes, and then buffers and aggregates the uncertainty across a tessellation grid. The tessellation grid can then be visualized by any of the statistical fields generated. This toolbox can be applied to any geologic map database adhering to the GeMS format to produce visualizations summarizing uncertainty. While there is still much we can do to refine how we quantify uncertainty in mapping geologic features, this type of visualization, when provided alongside the geologic map data, summarizes the uncertainty without requiring the user to understand the nuances of traditional map cartography. Additionally, this quantitative approach can help identify areas characterized by high levels of uncertainty, potentially a result of low-resolution map data, that can be used for geologic mapping needs assessments and to better inform end users to limit improper use of the map data.

Geological Society of America Abstracts with Programs. Vol. 54, No. 6

doi: 10.1130/abs/2022AM-380116

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