Water surface mapping from airborne laser scanning using signal intensity and elevation data
In recent years airborne laser scanning (ALS) evolved into a state-of-the-art technology for topographic data acquisition. We present a novel, automatic method for water surface classification and delineation by combining the geometrical and signal intensity information provided by ALS. The reflecti...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
30 September 2009
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| In: |
Earth surface processes and landforms
Year: 2009, Jahrgang: 34, Heft: 12, Pages: 1635-1649 |
| ISSN: | 1096-9837 |
| DOI: | 10.1002/esp.1853 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/esp.1853 Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/esp.1853 
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| Verfasserangaben: | Bernhard Höfle, Michael Vetter, Norbert Pfeifer, Gottfried Mandlburger, and Johann Stötter |
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| 245 | 1 | 0 | |a Water surface mapping from airborne laser scanning using signal intensity and elevation data |c Bernhard Höfle, Michael Vetter, Norbert Pfeifer, Gottfried Mandlburger, and Johann Stötter |
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| 520 | |a In recent years airborne laser scanning (ALS) evolved into a state-of-the-art technology for topographic data acquisition. We present a novel, automatic method for water surface classification and delineation by combining the geometrical and signal intensity information provided by ALS. The reflection characteristics of water surfaces in the near-infrared wavelength (1064 nm) of the ALS system along with the surface roughness information provide the basis for the differentiation between water and land areas. Water areas are characterized by a high number of laser shot dropouts and predominant low backscatter energy. In a preprocessing step, the recorded intensities are corrected for spherical loss and atmospheric attenuation, and the locations of laser shot dropouts are modeled. A seeded region growing segmentation, applied to the point cloud and the modeled dropouts, is used to detect potential water regions. Object-based classification of the resulting segments determines the final separation of water and non-water points. The water-land-boundary is defined by the central contour line of the transition zone between water and land points. We demonstrate that the proposed workflow succeeds for a regulated river (Inn, Austria) with smooth water surface as well as for a pro-glacial braided river (Hintereisfernerbach, Austria). A multi-temporal analysis over five years of the pro-glacial river channel emphasizes the applicability of the developed method for different ALS systems and acquisition settings (e.g. point density). The validation, based on real time kinematic (RTK) global positioning system (GPS) field survey and a terrestrial orthophoto, indicate point cloud classification accuracy above 97% with 0·45 m planimetric accuracy (root mean square error) of the water-land boundary. This article shows the capability of ALS data for water surface mapping with a high degree of automation and accuracy. This provides valuable datasets for a number of applications in geomorphology, hydrology and hydraulics, such as monitoring of braided rivers, flood modeling and mapping. Copyright © 2009 John Wiley & Sons, Ltd. | ||
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