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| Titel |
A new processing strategy for CryoSat-2 SAR data over lakes based on waveform classification, sub-waveform retracking and outlier rejection |
| VerfasserIn |
Franziska Göttl, Denise Dettmering, Felix Lucian Müller, Christian Schwatke |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250147727
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| Publikation (Nr.) |
 EGU/EGU2017-11930.pdf |
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| Zusammenfassung |
| The estimation of lake water level variations with satellite altimetry is a challenging task because the majority of altimeter waveforms of smaller lakes are contaminated by land. In this study we used CryoSat-2 SAR data to estimate reliable water level time series for the four lakes: Tonle Sap (Cambodia), Vättern (Sweden), Okeechobee (Florida, USA) and Lough Neagh (North Ireland) with different size, surrounding landscape and water oscillation. Therefor a novel processing strategy was developed based on waveform classification, sub-waveform retracking and outlier rejection. The classification of waveforms is essential to find out which observations are performed over water and at the land-water transition. For this purpose, in a training area CryoSat-2 SAR waveforms were grouped into clusters with respect to the similarity of the amplitude, width and center of gravity of the waveforms by using the k-means algorithm. Especially for waveforms at the land-water transition the identification of the “best” sub-waveform becomes very important. The results are validated with modeled water heights derived from CryoSat-2 SAR data, multi-mission water level time series from classical altimetry and in-situ gauging data. The CryoSat-2 time series show similar quality although in our approach no model assumptions are applied. Especially for smaller lakes water heights can be derived from CryoSat-2 SAR data with higher precision than from classical altimeter data. |
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