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Machine Learning Tools for Automatic Mapping of Martian Landforms
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2007.114November/December 2007 (vol. 22 no. 6) pp. 100-106
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Tomasz Stepinski, Ricardo Vilalta, Soumya Ghosh, "Machine Learning Tools for Automatic Mapping of Martian Landforms," IEEE Intelligent Systems, vol. 22, no. 6, pp. 100-106, November/December, 2007.
 
 
BibTex
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@article{ 10.1109/MIS.2007.114,
author = {Tomasz Stepinski and Ricardo Vilalta and Soumya Ghosh},
title = {Machine Learning Tools for Automatic Mapping of Martian Landforms},
journal ={IEEE Intelligent Systems},
volume = {22},
number = {6},
issn = {1541-1672},
year = {2007},
pages = {100-106},
doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2007.114},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Intelligent Systems
TI - Machine Learning Tools for Automatic Mapping of Martian Landforms
IS - 6
SN - 1541-1672
SP100
EP106
EPD - 100-106
A1 - Tomasz Stepinski,
A1 - Ricardo Vilalta,
A1 - Soumya Ghosh,
PY - 2007
KW - machine learning
KW - Mars
VL - 22
JA - IEEE Intelligent Systems
ER -
 
Tomasz Stepinski, Lunar and Planetary Institute
Ricardo Vilalta, University of Houston
Soumya Ghosh, University of Colorado
The Mars planetary missions have produced vast stores of science data. The authors describe machine-learning methods and tools they've used to automate geomorphic mapping of Mars from archived data.

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[1] B.D. Bue and T.F. Stepinski, "Automated Classification of Landforms on Mars," Computers &Geoscience, vol. 32, no. 5, 2006, pp. 604–614.
[1] D. Smith et al., Mars Global Surveyor Laser Altimeter Mission Experiment Gridded Data Record, NASA Planetary Data System, MGS-M-MOLA-5-MEGDR-L3-V1.0, 2003; www.gps.caltech.edu/~marsdatamars_MOLA_mgsl_300x_aareadme.txt .

Index Terms:
machine learning, Mars
Citation:
Tomasz Stepinski, Ricardo Vilalta, Soumya Ghosh, "Machine Learning Tools for Automatic Mapping of Martian Landforms," IEEE Intelligent Systems, vol. 22, no. 6, pp. 100-106, Nov./Dec. 2007, doi:10.1109/MIS.2007.114
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