Automated recognition of valley heads from digital elevation models

Automated recognition of valley heads from digital elevation models Applications of landform recognition in map‐making, geographical information systems, and in improving the storage and representation of earth surface information are described. Reasons are given for the use of digital elevation models for landform recognition: increasing availability of data, easier data integration, and automation of landform recognition. An automated technique for recognizing valley heads from digital elevation models is presented. The technique has been developed for valley head recognition because valley heads are known locations of geomorphological activity and because areal features have been largely ignored in the automated landform recognition literature. The problem of valley head recognition is divided into valley head location and valley head delineation, and the technique is developed using a DEM representing a simple artificial landscape. Two methods are given for valley head location. In the first, valley heads are located at valley ends. In the second, valley heads are located at cells which would have water flowing into them from many directions if water was flowing over the terrain. The latter method locates all the valley heads on the artificial landscape. The cells locating valley heads are iteratively ‘grown’ to adjacent cells that are concave in plan and not flat, to delineate the valley head. At best, 82 per cent valley head cells on the artificial landscape are correctly recognized with a 43 per cent commission error. The method is tested on real data where it is less successful because of the variability of real landscapes and the inadequacy of the methods chosen for valley network delineation. Machine learning of thresholds and a method involving inspection of profiles across a DEM cell are suggested as methods to improve the automated valley head recognition technique. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Earth Surface Processes and Landforms Wiley

Automated recognition of valley heads from digital elevation models

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Abstract

Applications of landform recognition in map‐making, geographical information systems, and in improving the storage and representation of earth surface information are described. Reasons are given for the use of digital elevation models for landform recognition: increasing availability of data, easier data integration, and automation of landform recognition. An automated technique for recognizing valley heads from digital elevation models is presented. The technique has been developed for valley head recognition because valley heads are known locations of geomorphological activity and because areal features have been largely ignored in the automated landform recognition literature. The problem of valley head recognition is divided into valley head location and valley head delineation, and the technique is developed using a DEM representing a simple artificial landscape. Two methods are given for valley head location. In the first, valley heads are located at valley ends. In the second, valley heads are located at cells which would have water flowing into them from many directions if water was flowing over the terrain. The latter method locates all the valley heads on the artificial landscape. The cells locating valley heads are iteratively ‘grown’ to adjacent cells that are concave in plan and not flat, to delineate the valley head. At best, 82 per cent valley head cells on the artificial landscape are correctly recognized with a 43 per cent commission error. The method is tested on real data where it is less successful because of the variability of real landscapes and the inadequacy of the methods chosen for valley network delineation. Machine learning of thresholds and a method involving inspection of profiles across a DEM cell are suggested as methods to improve the automated valley head recognition technique.

Journal

Earth Surface Processes and LandformsWiley

Published: Feb 1, 1991

References

  • Topographic partition of watersheds with digital elevation models
    Band, Band
  • Source areas, drainage density and channel initiation
    Montgomery, Montgomery; Dietrich, Dietrich
  • Variation of mainstream length with basin area
    Shreve, Shreve

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