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Session Chair: Karina Nielsen Session Chair: Pierre Féménias
10:40am - 11:00am
Markov Random Field Based Waveform Retracking Solved by the Graph Cuts Technique
Omid Elmi, Mohammad J. Tourian, Nico Sneeuw
Institute of Geodesy, University of Stuttgart, Germany
Application of satellite altimetry over inland water bodies requires a postprocessing algorithm known as retracking. This study introduces a new retracking algorithm that benefits from information about spatial and temporal variation of waveforms over the selected region. We stack the waveforms over a selected water body into radargrams for each overpass of altimetry, which we then segment and label into two distinct parts (before and after retracking gate) with the help of returned power and the contextual and temporal correlation in the radargram. The separation line between two segments is referred to as ‘’retracking line’’ which consists of the retracking gate for each waveform.
Markov random fields (MRF) can express a wide variety of spatially and temporally varying behaviors. To take advantages of this property, we define a MRF framework by specifying conditional distributions regarding the returned power and the labels. In order to find the retracking line in the radargram, the Maximum A Posteriori (MAP) estimate of the defined MRF must be sought. Since the high computational effort of finding a global solution is a serious concern, the problem is reshaped as an energy minimization problem. The minimum energy solution is found by the graph cuts technique, which is fast and able to find either the exact minimum or an approximate minimum solution. We apply our method to waveforms of the missions ENVISAT and CryoSat-2 over the Niger River at Lokoja and validate the corrected water level time series against in situ water level and discharge.
11:00am - 11:20am
Water Level Estimation Along The Mekong River Using Cryosat-2 SAR Multi-Look Stack Data
Eva Boergens1, Karina Nielsen2, Ole B. Andersen2, Denise Dettmering1, Florian Seitz1
1Deutsches Geodätisches Forschungsinstitut, Technische Universität München, München, Germany; 2Div. of Geodesy, DTU Space, National Space Institute, Kgs. Lyngby, Denmark.
Cryosat-2 SAR data is especially useful for monitoring smaller inland waters thanks to the improved along track resolution compared to conventional LRM altimetry. However, the extraction of reliable water levels is still challenging for smaller rivers where only very few consecutive measurements over the water body are present. Maps or land-water-masks are usually too unreliable for identifying small water bodies. Instead, altimetry measurements themselves can be used to detect the water measurements by means of classification processes.
The SAR data of Cryosat-2 contains all multi-looks for one point on the Earth’s surface in a so-called data stack. Each of the multi-looks is a returning waveform from a different looking angle. The SAR (multi-look) waveform is the averaged waveform of the stack. The assemblage of the mean power of each look is named RIP waveform. For our investigation, we use both quantities, i.e., the full stack data available for Cryosat-2 SAR, to classify the measurements and to identify the water returns. The classification is performed with a k-means clustering on features extracted from the waveform and the RIP waveform as well as the waveform and RIP waveform itself.
The classification approach is applied in the Mekong River basin. Out of ten clusters, those forming the water classes are identified in a test region with known river locations. These classes are used in a next step for grouping all measurements in the whole river basin in water and non-water measurements. The classified water measurements are used in a last step to generate water levels for each Cryosat-2 crossing with a river branch in the Mekong River basin.
The long repeat orbit of Cryosat-2, together with the complex topography of the region, hinders the extraction of water level time series at fixed virtual stations, which can be used for validation against in situ gauge data. Under the assumption of a very stable seasonal signal, which holds for the Mekong River, an internal validation of the data is possible. To this end, we compare, first, the water levels of consecutive passes (time difference 369 days) with each other and, second, water levels that are both close in location and close in season. The validation proves the success of the approach for the main river as well as for smaller tributaries.
11:20am - 11:40am
General Evaluation of the Performance of CryoSat-2 over Inland Water
Karina Nielsen, Ole B. Andersen, Lars Stenseng, Per Knudsen
Div. of Geodesy, National Space Institude, The Technical University of Denmark, Denmark
CryoSat-2 has now been operating for more than six years with the new altimeter modes SAR and SARIn. For inland water, studies have shown that water levels based on SAR and SARIn have shown improved results compared to conventional altimetry for selected lakes.
Here we perform a thorough investigation of the quality of obtained water levels from the SAR and SARIn modes from CryoSat-2. As part of the evaluation, we compare with results from conventional altimetry such as Envisat. We estimate the along-track precision of the mean and compare with in-situ data when possible. The water level is evaluated for various water bodies of different types and sizes and in different settings.