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| Titel |
Automatic channel network extraction from lidar through nonlinear diffusion and geodesic paths |
| VerfasserIn |
Paola Passalacqua, Efi Foufoula-Georgiou |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250044093
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| Zusammenfassung |
| An advanced methodology for channel network extraction is developed and implemented on several high resolution data sets of different characteristics, from a steep and landslide-dissected basin, to a mountainous region, to a flat and partly artificially drained area. The methodology incorporates nonlinear diffusion for the pre-processing of the data, both to focus the analysis on the scales of interest and to enhance features that are critical to the channel extraction. Following this pre-processing, channels are defined as curves of minimal effort, or geodesics, where the effort is measured based on fundamental geomorphological characteristics such as flow accumulation and iso-height contours curvature.
The results obtained show that the geometric nonlinear methodology is computationally efficient and able to achieve robust extraction of the channels. |
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