Paper No. 1
Presentation Time: 8:05 AM

PREDICTING VENUSIAN SHIELD FIELD ORIENTATIONS USING A MATLAB-DERIVED STATISTICAL TOOL


LANG, N.P., Department of Geology, Mercyhurst University, Erie, PA 16546, THOMSON, Bradley James, Center for Remote Sensing, Boston University, 725 Commonwealth Ave., Room 433, Boston, MA 02215 and KELLY, Nicholas, Department of Geology, Mercyhurst University, 501 East 38th Street, Erie, PA 16546, nlang@mercyhurst.edu

Shield fields are clusters of small (<20 km in diameter and <<1 km in height) volcanic edifices that occur across the Venusian surface. Individual edifices (or shields) within a single field reside at the effective resolution of Magellan Synthetic Aperture Radar (SAR) imagery (resolution of ~75 m/pixel), which makes unraveling the formational controls on shield fields and developing a shield field stratigraphy challenging. However, given the widespread occurrence of shields across the Venusian surface, constraining formational controls and a stratigraphy within individual fields may provide a critical window for understanding Venus’ volcanic (and possibly tectonic) history. To better understand histories recorded at individual fields, we have applied a recently developed MATLAB® (MATrix LABoratory)-derived statistical tool to examine potential vent alignments within four shield fields – Chernava (10.5° S, 335° E), Ran (0° N, 162° E), Urutonga (12.5° N, 152° E), and Jurate (57° N, 153° E) collis. The statistical tool employs the two-point azimuth method and Monte Carlo techniques in an algorithm incorporated into a GUI where a user selects pre-processed input data, which is a CSV file containing the lat, lon position of each edifice in a field. The main body of the GUI consists of three panels: 1) the distribution of shields as shown in an x-y scatter plot; 2) a raw, uncorrected histogram of orientation measurements; 3) a “normalized” histogram showing the results produced from a user-specified number of Monte Carlo runs. To determine if model-derived values are statistically significant to the 95% significance level, the Student's t distribution is used to determine the 95th percentile critical threshold value. Values exceeding the critical threshold value are deemed statistically significant. Applying this model to our four targeted fields yields results consistent with tectonic structure trends in each area, which gives us confidence this statistical model works. The results also allow us to qualitatively highlight (recent?) regional stress orientations on Venus and understand the conditions that influenced the evolution of each field. Future work will also examine potential small-scale (i.e., not whole-field) preferred orientations to help refine the volcanic stratigraphy recorded within each field.