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Automated Identification and Characterization of Landforms on Mars
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| We propose development, implementation, testing, and application of novel methods for automated identification and analysis of selected landforms on Mars. Because of the large and increasing volume of Martian data such automated techniques are essential for thorough data analysis. In particular, we will implement algorithms for an identification and characterization of Martian impact craters and valley networks. In a major break with the past attempts to automate identification of landforms on planetary surface, the proposed algorithms are based on digital elevation data instead of imagery data. Using a fusion of methods from the fields of digital terrain analysis, data mining, and computer vision, we will produce production grade, fully autonomous algorithms. The crater identification algorithm will be used to construct a catalog of Martian craters that, in addition to craters coordinates, lists all their physical parameters. Such catalog would be an invaluable resource for a range of Martian studies. The valley networks mapping algorithm will be used to map drainage systems and to produce continuous maps of drainage density. These are important resources in the studies of past Martian climate. The proposal offers proof-of-concept results for these two algorithms. In addition, we propose to improve on our recently developed method for a general, unsupervised landform classifier, which subdivides Martian landscape into constituent landforms. We will employ the technique of semi-supervised clustering to increase the accuracy of the original classifier. We expect that the new classifier will provide, among other benefits, an alternative method for crater identification and analysis. The methods developed in the proposed research are applicable to other bodies in the Solar System, such as the Earth, the Moon, and Mercury, for which the topography data is available, or is about to become available. By automating analysis of some of the most interesting landforms on Mars, the proposed research increases efficiency of the Science Mission Directorate research, which is one of the goals of the AISRP. It is highly relevant to the NASA objective of thorough study of planet Mars. |
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