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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,

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Presentation on theme: "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,"— Presentation transcript:

1 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

2 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

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

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

5 RC/OpNav data analysis Geological Society of America — Denver, CO, 28 October 2013 Image credit: NASA/JPL/DLR OpNav data from Vesta’s south pole (left), and RC1 image f2_ taken of region near Marcia crater (right).

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

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

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

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

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

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

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

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

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

15 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

16 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

17 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. Thanks to the Dawn operational, instrument and science teams! This work was funded through the NASA Dawn at Vesta Participating Scientist Program Acknowledgements Geological Society of America — Denver, CO, 28 October 2013


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