Channel network extraction from high resolution topography using wavelets

Authors

  • Bruno Lashermes,

    1. National Center for Earth-Surface Dynamics and St. Anthony Falls Laboratory, Department of Civil Engineering, University of Minnesota, Minneapolis, Minnesota, USA
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  • Efi Foufoula-Georgiou,

    1. National Center for Earth-Surface Dynamics and St. Anthony Falls Laboratory, Department of Civil Engineering, University of Minnesota, Minneapolis, Minnesota, USA
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  • William E. Dietrich

    1. Department of Earth and Planetary Science, University of California, Berkeley, California, USA
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Abstract

[1] The availability of high resolution topography from LIDAR offers new opportunities for objectively extracting the channels directly from a DEM using local topographic information, instead of inferring them indirectly based on global criteria, such as area or area-slope threshold relationships. Here we introduce the use of wavelet filtering to delineate threshold curvatures for defining valleys and threshold slope-direction-change for defining probable channeled portions of the valleys. This approach exploits the topographic signatures uniquely found in high resolution topography, and reveals the fuzzy topographic transition in which local weakly convergent areas lie at the transition between hillslopes and valleys.

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