Geologic Mapping Methods for a MissionDriven Mapping Scenario

Outline Emphasis here is on the process of geologic mapping in the context of

Background Color-shaded relief map of Vesta, showing prominent features. Topography derived from Dawn Framing

Iterative mapping Orbital stages of the Dawn at Vesta mission. ~400 m/pxl ~250 m/pxl

RC/Op. Nav data analysis Op. Nav data from Vesta’s south pole (left), and RC

RC/Op. Nav-based map ~400 m/pxl Geologic map based on RC and Op. Nav data.

RC/Op. Nav data analysis Marcia RC 3 data covering Vesta’s equator from Divalia Fossae

Survey data analysis Survey data covering Vesta’s equator (above) and south pole (left). Geological

Geologic map based on Survey data. Map created in Arc. GIS; base is a

Units Cratered plains (left) and cratered highlands (bottom), both located in Vestalia Terra. Geological

Units Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Units Mass-wasting and smooth material, Marcia Crater. Aricia Tholus, Geological Society of America —

HAMO data analysis HAMO data covering Vesta’s south pole. Geological Society of America —

HAMO-based map Geologic map based on HAMO data. Map created in Arc. GIS; base

Lessons Learned 1 Iterative process driven primarily by rapid data acquisition, and the consequent

Lessons Learned 2 Topography more definitive than morphology in defining units. Lack of definitive

Summary Iterative mapping can provide an orbiting spacecraft team with reasonable geologically-based proto-units in

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Geologic Mapping Methods for a Mission-Driven Mapping Scenario: The Dawn at Vesta Example R. A. Yingst, S. C. Mest, D. A. Williams, W. B. Garry, D. C. Berman, C. M. Pieters, R. Jaumann, C. T. Russell, C. A. Raymond, and the Dawn Science Team Geological Society of America 28 October 2013

Outline Emphasis here is on the process of geologic mapping in the context of an active spacecraft mission First - Prior work and data flow Second - Iterations of the map Third - Lessons learned: Mapping process: Time pressures meant overthinking minimized, but shortcuts retained too long. Mapping Vesta: Topography more definitive than morphology in defining units. Geological Society of America — Denver, CO, 28 October 2013

Background Color-shaded relief map of Vesta, showing prominent features. Topography derived from Dawn Framing Camera data. Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Iterative mapping Orbital stages of the Dawn at Vesta mission. ~400 m/pxl ~250 m/pxl ~60 m/pxl Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

RC/Op. Nav data analysis Op. Nav data from Vesta’s south pole (left), and RC 1 image f 2_362695687 taken of region near Marcia crater (right). Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

RC/Op. Nav-based map ~400 m/pxl Geologic map based on RC and Op. Nav data. Map created in Adobe Illustrator; base is a Framing Camera mosaic at ~ 400 m/pxl resolution. Map at ~ 1: 20 M scale. Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

RC/Op. Nav data analysis Marcia RC 3 data covering Vesta’s equator from Divalia Fossae to Marcia, Calpurnia and Minucia craters. Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Survey data analysis Survey data covering Vesta’s equator (above) and south pole (left). Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Geologic map based on Survey data. Map created in Arc. GIS; base is a Framing Camera mosaic at ~ 250 m/pxl resolution. Map at 1: 1 M scale. Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Units Cratered plains (left) and cratered highlands (bottom), both located in Vestalia Terra. Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Units Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Units Mass-wasting and smooth material, Marcia Crater. Aricia Tholus, Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

HAMO data analysis HAMO data covering Vesta’s south pole. Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

HAMO-based map Geologic map based on HAMO data. Map created in Arc. GIS; base is a Framing Camera mosaic at ~ 60 m/pxl resolution. 1: 500, 000 Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR

Lessons Learned 1 Iterative process driven primarily by rapid data acquisition, and the consequent need to generate new products quickly. Process needs multiple, experienced workers. Compressed timeline meant less overthinking of results and interpretations… …but also overuse of standard symbology and nomenclature. Geological Society of America — Denver, CO, 28 October 2013

Lessons Learned 2 Topography more definitive than morphology in defining units. Lack of definitive interpretations of spectral data hampered unit definition. Geological Society of America — Denver, CO, 28 October 2013

Summary Iterative mapping can provide an orbiting spacecraft team with reasonable geologically-based proto-units in a timely manner. Experience and multiple workers crucial to meet the timeline. Time pressures meant overthinking minimized, but shortcuts retained too long. Topography more definitive than morphology in defining units. Multispectral data crucial in making interpretations of units. Acknowledgements • Thanks to the Dawn operational, instrument and science teams! • This work was funded through the NASA Dawn at Vesta Participating Scientist Program Geological Society of America — Denver, CO, 28 October 2013