Gigapixel imaging as a resource for geoscience teaching, research, and outreach

Abstract:

The Mid-Atlantic Geo-Image Collection is a repository of gigapixel-resolution geologic imagery intended as a tool for geoscience professionals, educators, students, & researchers (http://gigapan.com/groups/100/galleries). GigaPan provides a unique combination of context & detail, with images that maintain a high level of resolution through every level of magnification. Using geological GigaPans, physically disabled students can participate in virtual field trips, instructors can bring inaccessible outcrops into the classroom, & students can zoom in on hand samples without expensive microscopes. Because GigaPan images permit detailed visual examination of geologic, MAGIC is particularly suitable for use in online geology courses. The images are free to use and tag.

Our 10 contributors (3 faculty, 2 graduate students, & 6 undergraduates) use 4 models of mobile robot cameras (outcrop/landscape), 2 laboratory-based GIGAmacro imaging systems (hand samples) & 2 experimental units: 1 for thin sections, 1 for GigaPans of scanning electron microscopy. Each of these has strengths & weaknesses.

MAGIC has suites of images of Appalachian structure & stratigraphy, Rocky Mountains, Snowball Earth hypothesis, & doomed outcrops of Miocene strata on Chesapeake Bay. Virtual field trips with our imagery have been developed for: Billy Goat Trail, MD; Helen Lake, AB; Wind River Canyon, WY; the Canadian Rockies; El Paso, TX; glaciation around the world; and Corridor H, WV (a GSA field trip in Nov. 2015). Virtual sample sets have been developed for introductory minerals, igneous, sedimentary, & metamorphic rocks, the stratigraphy of VA’s physiographic provinces, & the Snowball Earth hypothesis. The virtual field trips have been tested in both online & onsite courses. There are close to a thousand images in the collection, each averaging about 0.9 gigapixels in size, with close to 900,000 views total.

A new viewer for GigaPans was released this year by GIGAmacro. This new viewer allows measurement and calibration, automatically resizing scale bars, side-by-side comparisons between 2 images, overlapping presentation of 2 images, & annotation by users. Comparative viewers are particularly useful for the presentation of before/after imagery; raw vs. annotated imagery, & polarized views of thin sections.