The Performance of Altimeter Waveform Retrackers at Lake Baikal

Yi, Yuchan; Kouraev, Alexei V.; Shum, C. K.; Vuglinsky, Valery; Crétaux, Jean-François; Calmant, Stéphane

doi:10.3319/tao.2012.10.09.01(tibxs)

Cited by 17 publications

(12 citation statements)

References 18 publications

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“…Radar altimetry is a promising technique for directly detecting water level [14][15][16], but the application of this technique to monitor inland waters has several limitations [17,18]. For one thing, it is difficult to analyze altimetry waveforms over a complex, varying surface [19,20]. For another, altimetry is a profiling technique, not an imaging technique; it can only provide a limited footprint of a lake and is unable to depict overall spatial distribution on a regional scale [21,22].…”

Section: Introductionmentioning

confidence: 99%

Combining Multispectral Imagery with in situ Topographic Data Reveals Complex Water Level Variation in China’s Largest Freshwater Lake

Liu

2015

Remote Sensing

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Lake level variation is an important hydrological indicator of water balance, biodiversity and climate change in drainage basins. This paper illustrates the use of moderate-resolution imaging spectroadiometer (MODIS) data to characterize complex water level variation in Poyang Lake, the largest freshwater lake in China. MODIS data were used in conjunction with in situ topographic data, otherwise known as the land-water contact method, to investigate the potential of this hybrid water level spatiotemporal variability measurement technique. An error analysis was conducted to assess the derived water level relative to gauge data. Validation results demonstrated that the land-water contact method can satisfactorily capture spatial patterns and seasonal variations in water level fluctuations. The correlation coefficient ranged from 0.684 to 0.835, the root-mean-square-error from 0.79 m-1.09 m, and the mean absolute bias error from 0.65 m to 0.86 m for five main gauge stations surrounding the lake. Additionally, seasonal and interannual variations in the lake's water level were revealed in the MODIS-based results. These results indicate that the land-water contact method has the potential to be applied in mapping water level changes in Poyang Lake. This study not only provides a foundation for basic hydrological and ecological studies, but is also valuable for the conservation and management of water resources over gauge-sparse regions in Poyang Lake. OPEN ACCESSRemote Sens. 2015, 7 13467

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Section: Introductionmentioning

confidence: 99%

Combining Multispectral Imagery with in situ Topographic Data Reveals Complex Water Level Variation in China’s Largest Freshwater Lake

Liu

2015

Remote Sensing

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“…Since the middle of the 1990's, satellite radar altimetry has been a successful technique for monitoring height variations of continental surface water, such as lakes and rivers (Morris and Gill 1994;Alsdorf et al 2001;Calmant et al 2008;Abarca-del-Rio et al 2012;Sima et al 2013;Yi et al 2013;Silva et al 2014;Pandey et al 2014;Tarpanelli et al 2015 and many others). The surface water level is measured within a terrestrial reference frame with repeatability varying from 10 to 35 days depending on the orbit cycle of the satellite.…”

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confidence: 99%

Lake Volume Monitoring from Space

Crétaux¹,

et al. 2016

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Lakes are integrators of environmental change occurring at both the regional and global scale. They present a wide range of behavior on a variety of timescales (cyclic and secular) depending on their morphology and climate conditions. Lakes play a crucial role in retaining and stocking water, and because of the significant global environmental changes occurring at several anthropocentric levels, the necessity to monitor all morphodynamic characteristics [e.g., water level, surface (water contour) and volume] has increased substantially. Satellite altimetry and imagery are now widely used together to calculate lake and reservoir water storage changes worldwide. However, strategies and algorithms to calculate these characteristics are not straightforward, and specific approaches need to be developed. We present a review of some of these methodologies by using lakes over the Tibetan Plateau to illustrate some critical aspects and issues (technical and scientific) linked to the observation of climate change impact on surface waters from remote sensing data. Many authors have measured water variation using the limited remote sensing measurements available over short time periods, even though the time series are probably too short to directly link these results with climate change. Indeed, there are many processes and factors, like the influence of lake morphology, that are beyond observation and are still uncertain. The time response for lakes to reach a new state of equilibrium is a key aspect that is often neglected in current literature. Observations over a long period of time, including maintaining a constellation of comprehensive and complementary satellite missions with service continuity over decades, are therefore necessary especially when the ground gauge network is too limited. In addition, the design of future satellite missions with new instrumental concepts (e.g., SAR, SARin, Ka band altimetry, Ka interferometry) will also be suitable for complete monitoring of continental waters.

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“…Range values that are derived from the Offset Center Of Gravity (OCOG) retracker [28] are used to estimate altimeter height. Ranges derived from this retracker, rather than from Ocean retracker, also present in the GDR, were chosen as it was found to be robust and to provide accurate values of water levels over inland water bodies [9,11,29,30]. As presented in equation 3, conventional corrections use Wet tropospheric corrections Corr wtropo (atmospheric refraction range delay due to water vapour and cloud liquid water content of the troposphere), Dry tropospheric correction Corr dtropo (atmospheric refraction range delay due to the dry gas component of the troposphere), Ionospheric correction Corr iono (atmospheric refraction range delay due to the free electron content associated with dielectric properties of the ionosphere), and the corrections that respectively account for crustal vertical motions that are due to solid Earth Tide earth and polar Tide pole tides [31].…”

Section: Preliminary Processing Using Mapsmentioning

confidence: 99%

Improving the Estimation of Water Level over Freshwater Ice Cover using Altimetry Satellite Active and Passive Observations

et al. 2020

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Owing to its temporal resolution of 10-day and its polar orbit allowing several crossings over large lakes, the US National Aeronautics and Space Administration (NASA) and the French Centre National d’Etudes Spatiales (CNES) missions including Topex/Poseidon, Jason-1/2/3 demonstrated strong capabilities for the continuous and long-term monitoring (starting in 1992) of large and medium-sized water bodies. However, the presence of heterogeneous targets in the altimeter footprint, such as ice cover in boreal areas, remains a major issue to obtain estimates of water level over subarctic lakes of similar accuracy as over other inland water bodies using satellite altimetry (i.e., R ≥ 0.9 and RMSE ≤ 10 to 20 cm when compared to in-situ water stages). In this study, we aim to automatically identify the Jason-2 altimetry measurements corresponding to open water, ice and transition (water-ice) to improve the estimations of water level during freeze and thaw periods using only the point measurements of open water. Four Canadian lakes were selected to analyze active (waveform parameters) and passive (brightness temperature) microwave data acquired by the Jason-2 radar altimetry mission: Great Slave Lake, Lake Athabasca, Lake Winnipeg, and Lake of the Woods. To determine lake surface states, backscattering coefficient and peakiness at Ku-band derived from the radar altimeter waveform and brightness temperature at 18.7 and 37 GHz measured by the microwave radiometer contained in the geophysical data records (GDR) of Jason-2 were used in two different unsupervised classification techniques to define the thresholds of discrimination between open water and ice measurements. K-means technique provided better results than hierarchical clustering based upon silhouette criteria and the Calinski-Harabz index. Thresholds of discrimination between ice and water were validated with the Normalized Difference Snow Index (NDSI) snow cover products of the MODIS satellite. The use of open water threshold resulted in improved water level estimation compared to in situ water stages, especially in the presence of ice. For the four lakes, the Pearson coefficient (r) increased on average from about 0.8 without the use of the thresholds to more than 0.90. The unbiased RMSE were generally lower than 20 cm when the threshold of open water was used and more than 22 cm over smaller lakes, without using the thresholds.

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The Performance of Altimeter Waveform Retrackers at Lake Baikal

Cited by 17 publications

References 18 publications

Combining Multispectral Imagery with in situ Topographic Data Reveals Complex Water Level Variation in China’s Largest Freshwater Lake

Combining Multispectral Imagery with in situ Topographic Data Reveals Complex Water Level Variation in China’s Largest Freshwater Lake

Lake Volume Monitoring from Space

Improving the Estimation of Water Level over Freshwater Ice Cover using Altimetry Satellite Active and Passive Observations

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