geologic mapping methods for a mission-driven mapping scenario: the dawn at vesta example r. a....

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 America28 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

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.

Iterative mapping


Orbital stages of the Dawn at Vesta mission.

~400 m/pxl

~250 m/pxl

~60 m/pxl

RC/OpNav data analysis


OpNav data from Vesta’s south pole (left), and RC1 image f2_362695687 taken of region near Marcia crater (right).

RC/OpNav-based map


~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.

RC/OpNav data analysis


RC 3 data covering Vesta’s equator from Divalia Fossae to Marcia, Calpurnia and Minucia craters.

Marcia

Survey data analysis


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


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.

Units


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

Image credit: NASA/JPL/DLR

Units


Units


Mass-wasting and smooth material, Marcia Crater.

Image credit: NASA/JPL/DLR

Aricia Tholus,

HAMO data analysis


HAMO data covering Vesta’s south pole.

HAMO-based map


Geologic map based on HAMO data. Map created in ArcGIS; base is a Framing Camera mosaic at ~ 60 m/pxl resolution. 1:500,000

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.


Lessons Learned 2

Topography more definitive than morphology in defining units.

Lack of definitive interpretations of spectral data hampered unit definition.


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


geologic mapping methods for a mission-driven mapping scenario: the dawn at vesta example r. a....

Documents

nasajpldlr slide

image credit

mpxl slide

nasajpldlr hamo data

nasajpldlr survey data

nasajpldlr geologic

nasajpldlr opnav data

marcia slide