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Computers & Geosciences
Volume 32, Issue 5, June 2006, Pages 604-614
 
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doi:10.1016/j.cageo.2005.09.004    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2005 Elsevier Ltd All rights reserved.

Automated classification of landforms on Mars

B.D. Buea and T.F. Stepinskib, Corresponding Author Contact Information, E-mail The Corresponding Author

aDepartment of Computer Science, Purdue University, 250 N. University St., West Lafayette, IN 47907, USA bLunar and Planetary Institute, 3600 Bay Area Blvd., Houston, TX 77058, USA

Received 25 February 2005; 
revised 7 September 2005; 
accepted 7 September 2005. 
Available online 9 November 2005.

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Abstract

We propose a numerical method for classification and characterization of landforms on Mars. The method provides an alternative to manual geomorphic mapping of the Martian surface. Digital elevation data is used to calculate several topographic attributes for each pixel in a landscape. Unsupervised classification, based on the self-organizing map technique, divides all pixels into mutually exclusive and exhaustive landform classes on the basis of similarity between attribute vectors. The results are displayed as a thematic map of landforms and statistics of attributes are used to assign semantic meaning to the classes. This method is used to produce a geomorphic map of the Terra Cimmeria region on Mars. We assess the quality of the automated classification and discuss differences between results of automated and manual mappings. Potential applications of our method, including crater counting, landscape feature search, and large scale quantitative comparisons of Martian surface morphology, are identified and evaluated.

Keywords: Landform classification; Self-organizing maps; Digital topography models; Automated techniques; Mars

Article Outline

1. Introduction
2. Topographic attributes for Martian surfaces
3. Methods
4. Classification of landforms in Terra Cimmeria, Mars
5. Review of Terra Cimmeria results
6. Discussion and conclusions
Acknowledgements
References







Computers & Geosciences
Volume 32, Issue 5, June 2006, Pages 604-614
 
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