Associate Professor Xiaoli Deng

© 2016 Elsevier B.V.Satellite altimetry has proven a valuable resource of information on river and lake levels where in situ data are sparse or non-existent. In this study several new methods for obtaining stable inland water levels from CryoSat-2 Synthetic Aperture Radar (SAR) altimetry are presented and evaluated. In addition, the possible benefits from combining physical and empirical retrackers are investigated.The retracking methods evaluated in this paper include the physical SAR Altimetry MOde Studies and Applications (SAMOSA3) model, a traditional subwaveform threshold retracker, the proposed Multiple Waveform Persistent Peak (MWaPP) retracker, and a method combining the physical and empirical retrackers. Using a physical SAR waveform retracker over inland water has not been attempted before but shows great promise in this study.The evaluation is performed for two medium-sized lakes (Lake Vänern in Sweden and Lake Okeechobee in Florida), and in the Amazon River in Brazil. Comparing with in situ data shows that using the SAMOSA3 retracker generally provides the lowest root-mean-squared-errors (RMSE), closely followed by the MWaPP retracker. For the empirical retrackers, the RMSE values obtained when comparing with in situ data in Lake Vänern and Lake Okeechobee are in the order of 2-5 cm for well-behaved waveforms. Combining the physical and empirical retrackers did not offer significantly improved mean track standard deviations or RMSEs. Based on these studies, it is suggested that future SAR derived water levels are obtained using the SAMOSA3 retracker whenever information about other physical properties apart from range is desired. Otherwise we suggest using the empirical MWaPP retracker described in this paper, which is both easy to implement, computationally efficient, and gives a height estimate for even the most contaminated waveforms.

© 2016 IEEE.Over inland waters the altimetry radar return is typically contaminated by both land and surrounding vegetation. Moreover, the radar returns corresponding to floodplain vegetation and exposed mud flats can have similar waveform shapes to those reflected from open water surfaces so that the derived water surface elevations are either inaccurate or difficult to extract. This letter presents a robust and automated method based on image analysis of satellite imagery for the selection of altimetry waveforms over inundated zones. The altimetry footprint is assessed as being inundated if the radiometric response of an image kernel within the footprint conforms to known remotely sensed responses for water. The method was applied in the lower middle Fly floodplain of the Fly River in the Western Province of Papua New Guinea (PNG). Altimetry waveforms were assessed for inundation extent and vegetation cover, with those that met threshold levels being flagged for further retracking and water surface elevation monitoring. The results show that the method accurately identified> 90% of inundated sites along altimeter ground tracks and correctly selected waveforms reflected from water surfaces.

© Springer International Publishing Switzerland 2015.This paper investigates the capability of observing tropical cyclones using satellite radar altimetry. Two representative cyclones Yasi (February 2011) and Larry (March 2006) in the northeast Australian coastal area are selected based also on available tide gauge sea level measurements. It is shown that altimetry data can capture high water levels induced by Larry and Yasi through a careful re-processing and re-editing of the data. About 18 years of data from multi-satellite altimetry missions including TOPEX/Poseidon, Jason- 1 and Jason-2, and seven tide gauges around the northern Australian coast are integrated using a multivariate regression approach. The results reveal that the multi-regression model can, in general, explain >60% of sea level variances in the study area. The model is then validated using independent data from tide gauge in Townsville. The comparison results indicate that the high sea levels predicted by the model taken into account of both altimetry and tide-gauge data agree well with those observed at Townsville during cyclone Larry.