Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification
In this study, reliable water levels for four lakes are estimated based on an innovative processing strategy using a semi-automatic CryoSat-2 Synthetic Aperture Radar (SAR) multi-looked waveform classification. The selection of valid water returns is an essential step in inland altimetry application...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-10-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/8/11/885 |
| _version_ | 1798031571531333632 |
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| author | Franziska Göttl Denise Dettmering Felix L. Müller Christian Schwatke |
| author_facet | Franziska Göttl Denise Dettmering Felix L. Müller Christian Schwatke |
| author_sort | Franziska Göttl |
| collection | DOAJ |
| description | In this study, reliable water levels for four lakes are estimated based on an innovative processing strategy using a semi-automatic CryoSat-2 Synthetic Aperture Radar (SAR) multi-looked waveform classification. The selection of valid water returns is an essential step in inland altimetry applications. In order to identify reliable observations allowing for an accurate retracking, an unsupervised classification method for CryoSat-2 SAR multi-looked waveforms has been developed based on the k-mean algorithm. With this approach, changes in the water surface extent or surrounding inundation areas can be taken into account. In addition, a modified version of the Improved Threshold Retracker is developed in order to obtain optimal results for the lake heights. The used method is based on the identification of the optimal sub-waveform by employing height thresholds. The validation of the derived CryoSat-2 SAR time series with in-situ gauging data yields root mean square (RMS) differences between 3 and 90 cm for the different lakes. Compared to modeled CryoSat-2 water heights derived according to the approach used in the AltWater database our water level time series are slightly improved in terms of RMS accuracy but they contain more gaps due to the lack of reliable observations. In comparison with classical radar altimeter missions such as Envisat or Jason-2, the SAR-based time series show smaller RMS differences for the small lakes but larger RMS differences for the large lakes covered by multiple repeat missions. The presented innovative processing strategy can be easily adopted to other satellite altimetry SAR data such as from the new Sentinel-3 mission. |
| first_indexed | 2024-04-11T19:59:37Z |
| format | Article |
| id | doaj.art-de0d3db45e51434990981ead430bbf8c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T19:59:37Z |
| publishDate | 2016-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-de0d3db45e51434990981ead430bbf8c2022-12-22T04:05:43ZengMDPI AGRemote Sensing2072-42922016-10-0181188510.3390/rs8110885rs8110885Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform ClassificationFranziska Göttl0Denise Dettmering1Felix L. Müller2Christian Schwatke3Deutsches Geodätisches Forschungsinstitut, Technische Universität München, Arcisstraße 21, 80333 Munich, GermanyDeutsches Geodätisches Forschungsinstitut, Technische Universität München, Arcisstraße 21, 80333 Munich, GermanyDeutsches Geodätisches Forschungsinstitut, Technische Universität München, Arcisstraße 21, 80333 Munich, GermanyDeutsches Geodätisches Forschungsinstitut, Technische Universität München, Arcisstraße 21, 80333 Munich, GermanyIn this study, reliable water levels for four lakes are estimated based on an innovative processing strategy using a semi-automatic CryoSat-2 Synthetic Aperture Radar (SAR) multi-looked waveform classification. The selection of valid water returns is an essential step in inland altimetry applications. In order to identify reliable observations allowing for an accurate retracking, an unsupervised classification method for CryoSat-2 SAR multi-looked waveforms has been developed based on the k-mean algorithm. With this approach, changes in the water surface extent or surrounding inundation areas can be taken into account. In addition, a modified version of the Improved Threshold Retracker is developed in order to obtain optimal results for the lake heights. The used method is based on the identification of the optimal sub-waveform by employing height thresholds. The validation of the derived CryoSat-2 SAR time series with in-situ gauging data yields root mean square (RMS) differences between 3 and 90 cm for the different lakes. Compared to modeled CryoSat-2 water heights derived according to the approach used in the AltWater database our water level time series are slightly improved in terms of RMS accuracy but they contain more gaps due to the lack of reliable observations. In comparison with classical radar altimeter missions such as Envisat or Jason-2, the SAR-based time series show smaller RMS differences for the small lakes but larger RMS differences for the large lakes covered by multiple repeat missions. The presented innovative processing strategy can be easily adopted to other satellite altimetry SAR data such as from the new Sentinel-3 mission.http://www.mdpi.com/2072-4292/8/11/885radar altimetryinland waterCryoSat-2 SARwaveform classificationwater level time series |
| spellingShingle | Franziska Göttl Denise Dettmering Felix L. Müller Christian Schwatke Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification Remote Sensing radar altimetry inland water CryoSat-2 SAR waveform classification water level time series |
| title | Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification |
| title_full | Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification |
| title_fullStr | Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification |
| title_full_unstemmed | Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification |
| title_short | Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification |
| title_sort | lake level estimation based on cryosat 2 sar altimetry and multi looked waveform classification |
| topic | radar altimetry inland water CryoSat-2 SAR waveform classification water level time series |
| url | http://www.mdpi.com/2072-4292/8/11/885 |
| work_keys_str_mv | AT franziskagottl lakelevelestimationbasedoncryosat2saraltimetryandmultilookedwaveformclassification AT denisedettmering lakelevelestimationbasedoncryosat2saraltimetryandmultilookedwaveformclassification AT felixlmuller lakelevelestimationbasedoncryosat2saraltimetryandmultilookedwaveformclassification AT christianschwatke lakelevelestimationbasedoncryosat2saraltimetryandmultilookedwaveformclassification |