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| Titel |
Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data |
| VerfasserIn |
H. Zwenzner, S. Voigt |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 13, no. 5 ; Nr. 13, no. 5 (2009-05-11), S.567-576 |
| Datensatznummer |
250011857
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| Publikation (Nr.) |
 copernicus.org/hess-13-567-2009.pdf |
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| Zusammenfassung |
| Severe flood events turned out to be the most devastating catastrophes for
Europe's population, economy and environment during the past decades. The
total loss caused by the August 2002 flood is estimated to be 10 billion
Euros for Germany alone. Due to their capability to present a synoptic view
of the spatial extent of floods, remote sensing technology, and especially
synthetic aperture radar (SAR) systems, have been successfully applied for
flood mapping and monitoring applications. However, the quality and accuracy
of the flood masks and derived flood parameters always depends on the scale
and the geometric precision of the original data as well as on the
classification accuracy of the derived data products. The incorporation of
auxiliary information such as elevation data can help to improve the
plausibility and reliability of the derived flood masks as well as higher
level products. This paper presents methods to improve the matching of flood
masks with very high resolution digital elevation models as derived from
LiDAR measurements for example. In the following, a cross section approach
is presented that allows the dynamic fitting of the position of flood mask
profiles according to the underlying terrain information from the DEM. This
approach is tested in two study areas, using different input data sets. The
first test area is part of the Elbe River (Germany) where flood masks
derived from Radarsat-1 and IKONOS during the 2002 flood are used in
combination with a LiDAR DEM of 1 m spatial resolution. The other test data
set is located on the River Severn (UK) and flood masks derived from the
TerraSAR-X satellite and aerial photos acquired during the 2007 flood are
used in combination with a LiDAR DEM of 2 m pixel spacing. By means of these
two examples the performance of the matching technique and the scaling
effects are analysed and discussed. Furthermore, the systematic flood
mapping capability of the different imaging systems are examined. It could
be shown that the combination of high resolution SAR data and LiDAR DEM
allows the derivation of higher level flood parameters such as flood depth
estimates, as presented for the Severn area. Finally, the potential and the
constraints of the approach are evaluated and discussed. |
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