Digital Geology and Visualization

Professionals and students in the earth sciences use an array of graphs to study the earth. Earth scientists make use of a number of unique types of graphical formats that facilitate the representation and interpretation of data. For example, when describing the relationship between temperatures with depth in the earth, the traditional binary plot is rotated upside-down so that pressure (on the y-axis) increases downward, parallel to its orientation in the earth. Similar graph orientations are also used for plotting stratigraphic sections, depth-to-water tables, and metamorphic facies. These graphs present significant challenges to students learning but—once mastered—can foster new learning. In this companion poster presentation (see Lindgren and Wirth, this volume), we compare the eye-tracks of experts and novices when observing "bottleneck" graphs. We observe ordinal differences in eye-fixations between individuals in novice (undergraduate student) and expert (faculty and staff) groups. When asked to examine a graph without a prompt, the expert behavior is consistently systematic and deliberate, while the novice behavior is not. When novices and experts observe traditional binary line or scatter graphs under prompted conditions, the eye-tracks of individuals from both groups look more similar. Interestingly, the eye-track patterns of the individuals in the novice and expert groups diverge in response to non-traditional graph types (e.g., inverted binary plots, normalized plots, ternary plots). The comprehension accuracy of "bottleneck graphs" distinguishes those experts with heightened graphical capacity (regular disciplinary graph use) from those experts with "adaptive expertise" (those who do not regularly use graphs in their discipline). One explanation is that experts, with better-developed metacognitive or critical thinking skills, might be able to compensate for lack of familiarity in reading and comprehending new kinds of graphical information. We seek input from the community on other "bottleneck graphs" and interventions for improving student graph reading and comprehension.

Google Earth offers an engaging environment for exploration of earth science data by students at any level. The following GE layers (with data sources) have been collected/compiled by the author: 1) tectonic plate boundaries and plate names (Bird, 2003 model); 2) real-time earthquakes (USGS); 3) 30 years of M>=5.0 earthquakes, plotted by depth (USGS); 4) seafloor age (Mueller et al., 1997, 2008); 5) location and age data for hot spot tracks (published literature); 6) Holocene volcanoes (Smithsonian Global Volcanism Program); 7) GPS station locations with links to times series (JPL, NASA); 8) short-term motion vectors derived from GPS times series; 9) long-term average motion vectors derived from plate motion models (UNAVCO plate motion calculator); 10) earthquake data sets consisting of seismic station locations and links to relevant seismograms (Rapid Earthquake Viewer, USC/IRIS/DELESE). These layers, combined with simple spreadsheet and graphing tools, can be used for a wide variety of inquiry-based, data-rich exercises adaptable for introductory and upper-level activities. Exercises developed by the author are freely available for non-commercial use and include: exploration of topographic, seismic and volcanic characteristics of plate boundaries; determination and comparison of short-term and long-term average plate velocities; visualizing relative motion across plate boundaries; crustal strain analysis (modeled after the UNAVCO activity); and determining earthquake epicenters, body-wave magnitudes, and focal plane solutions. For example, students can use seafloor age data to determine plate velocities away from mid-ocean ridges. Or, students can use data from multiple hot spot tracks and make the case for stationary plumes/moving plates vs. stationary plates/moving plumes. And even at the introductory-level, students can visualize first P-wave motion patterns and relate focal plane solutions back to plate boundary settings.

Sketching is a common yet powerful means of communication and visualization in the geosciences. Particularly in field settings, geoscientists sketch in order to record data, explore interpretations, and communicate with peers. However, little prior work has examined the practice of field sketching, perhaps partly due to the "messy" nature of sketches as empirical data. Here, we describe how mixed methods were used to explore sketches made by expert geoscientists and non-geoscientists during a field trip to the Hat Creek fault zone (northern California, USA) taken as part of the 2013 AAPG Hedberg Research Conference. A total of 361 sketches of the normal fault system were collected from oil and gas industry geologists and seismic interpreters (n=20), academic geologists (n=16), and non-geoscientist software developers and cognitive scientists (n=6) during stops at three field modules. Sketches were first qualitatively analyzed by thematic coding to capture the range of sketch types (e.g., map, perspective landscape view, cross section, 3D block diagram) and annotations (e.g., fault symbols, reference locations, questions, edits, labels). The volume of sketches necessitated transforming qualitative data to a quantitative scheme in order to summarize results and compare sketching preferences across field trip stops and participant groups. Codes were counted and treated as nominal-level data. Differences in code frequency were tested for significance using the Pearson chi-square test of independence. Results suggest that sketching preferences appear to be largely driven by characteristics of the field trip stop and/or the particular task required. Few significant differences were found between groups, except that academic geoscientists more frequently drew related sets of 2D sketches whereas industry geoscientists more frequently edited and included text explaining their thinking. We offer this study as an example of how a mixed methods approach can be useful in exploring large yet "messy" datasets.

Understanding and appreciating the geographic terrain is a complex but necessary requirement for middle school aged (11-14yo) students. Abstract in nature, topographic maps and other 2D renderings of the Earth's surface and features do not address the inherent spatial challenges of a concrete-learner and traditional methods of teaching can at times exacerbate the problem. Technological solutions such as 3D-imaging in programs like Google Earth are effective but lack the tactile realness that can make a large difference in learning comprehension and retention for these young students. First developed in the 1980's, 3D printers were not commercial reality until recently and the rapid rise in interest has driven down the cost. With the advent of sub US00 3D printers, this technology has moved out of the high-end marketplace and into the local office supply store. Schools across the US and elsewhere in the world are adding 3D printers to their technological workspaces and students have begun rapid-prototyping and manufacturing a variety of projects. This project attempted to streamline the process of transforming data from a variety of formats (initially GeoTIFFS) based on the 2000 Shuttle Radar Topography Mission (SRTM) and the Global Multi-resolution Dataset (GMRT) by way of Python code. The resulting data was then inputted into a CAD-based program for visualization and exporting as a .stl file for 3D printing. A proposal for improving the method and making it more accessible to middle school aged students is provided. Using the SRTM data to print a hand-held visual representation of a portion of the Earth's surface would utilize existing technology in the school and alter how topography can be taught in the classroom. Combining methods of 2D paper representations, on-screen 3D visualizations, and 3D hand-held models, give students the opportunity to truly grasp and retain the information being provided.