A linear-time component-labeling algorithm using contour tracing technique
Computer Vision and Image Understanding
A new GRASS GIS toolkit for Hortonian analysis of drainage networks
Computers & Geosciences
Automatic recognition of landforms on mars using terrain segmentation and classification
DS'06 Proceedings of the 9th international conference on Discovery Science
Dynamic Landmarking for Surface Feature Identification and Change Detection
ACM Transactions on Intelligent Systems and Technology (TIST)
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Martian valley networks bear some resemblance to terrestrial drainage systems, but their precise origin remains an active research topic. A limited number of valley networks have been manually mapped from images, but the vast majority remains unmapped because standard drainage mapping algorithms are inapplicable to valleys that are poorly organized and lack spatial integration. In this paper, we present a novel drainage delineation algorithm specially designed for mapping the valley networks from digital elevation data. It first identifies landforms characterized by convex tangential curvature, and then uses a series of image processing operations to separate valleys from other features having a convex form. The final map is produced by reconnecting all valley segments along drainage directions. Eight test sites on Mars are selected and manually mapped for valley networks. The algorithm is applied to the test sites and delineated networks are compared to mapped networks using a series of quantitative quality factors. We have found a good agreement between delineated and mapped networks. In the process of comparing manual and delineated networks some shortcomings of manual mapping became apparent. We argue that delineated networks are indeed of better quality than the networks manually mapped from images. Although the algorithm has been developed to study Martian surface, it may also be relevant to terrestrial geomorphology.