06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
Browse
Search Results
Item Open Access CryoSat-2 for hydrological purposes : data processing, visualization and analysis(2013) Mayer, VolkerCryoSat-2, a remote sensing satellite of ESA, which is originally designed for the monitoring of sea and land ice surfaces, provides global radar altimetry data, that can also be used for other areas of application. This thesis will analyze its capability for hydrological studies of rivers, more precisely of their water level, extent and slope. For this purpose a GUI based on MATLAB, called CryoTrack, has been developed, which allows the operator to comprehend the tracks of the CryoSat-2 satellite on a global grid and to access their measurements for selected area and date. This data was used to determine water extent and slope of rivers, by combining the information of several radar altimetry quantities. Analyzing several intersections between the satellite tracks and the Niger River, algorithms for the designation of river width and slope were derived and tested for their capabilities and limitations. The transitions between water and land surfaces can be detected for wide rivers and their distance allows an estimation the river width. The moderate accuracy of this water extent calculation stands in contrast to the very good results of the slope computation between two or more intersections in the second part of the analysis.Item Open Access Application of spaceborne geodetic sensors for hydrology(2013) Tourian, Mohammad J.; Sneeuw, Nico (Prof. Dr.-Ing.)How much freshwater do we have on land? How is the freshwater cycle changing with time? Actually, we can not properly answer these questions as our knowledge of the spatial and temporal dynamics of the hydrological cycle is limited. The lack of knowledge is mainly induced by shortage of observational evidence, which motivates the objective of this study: the monitoring of the hydrological cycle using spaceborne geodetic sensors. Among the current space geodetic sensors, GRACE and satellite altimetry are the two active mission concepts, that can capture part of the hydrological cycle. However, monitoring the hydrological cycle using these two sensors is challenging. Satellite altimetry is investigated as an independent spaceborne sensor that provides the water level and discharge time series. An algorithm is developed to improve the quality of water level time series over inland water surfaces. This algorithm particularly deals with the challenges of resolution and uncertainty of altimetry. The obtained altimetric water level time series is validated against in situ measurements showing about 10% improvement in accuracy of the time series. Moreover, this study proposes an algorithm to reduce the random noise from pre-retracked data. The algorithm combines the results of different retrackers and provides water level time series with reduced noise level. The validation shows a significant reduction of noise level and a clear improvement in correlation with in situ measurements. Moreover, this study proposes a statistical approach based on quantile functions to infer a functional relationship between altimetric water level and in situ river discharge without the need for synchronous data sets. This method is based on a scatter diagram of quantile functions, in which the probability-coordinate is eliminated. In contrast, the conventional methods for simultaneous measurements operate directly on time series and eliminate the time-coordinate. The results show that the proposed methodology provides the same range of error as the common conventional empirical method. The good performance of the statistical approach supports the usage of altimetry to salvage pre-satellite altimetry discharge data and turn them into active use for the satellite altimetry time frame. In addition, a stochastic process model is implemented to (i) deal with the data outages in altimetric discharge, (ii) provide a scheme for data assimilation and (iii) smooth the discharge estimation. The model benefits from the cyclostationary behaviour of the discharge and is combined with the estimated discharge from altimetry and available in situ measurements to form a linear dynamic system. The dynamic system is solved using the Kalman filter, that provides an unbiased discharge with minimum variance. The error level of the results is comparable to the empirical approach. In this study, the utility of GRACE data as sensor of hydrological water storage changes is shown to be limited by the following challenges: consistency, resolution, separability and uncertainty. The challenge of inconsistency is addressed by developing two filters for hydrological and hydro-meteorological water storage changes, which lead to a better correlation with GRACE mass storage changes. The challenges of separability and resolution are not specifically investigated in this study, yet their consequences, which appear in different forms of uncertainties is investigated. To deal with the GRACE uncertainties, an algorithm is developed to detect outliers in monthly solutions. The outliers have been corrected by replacing them by an inter-annual monthly mean of the respective month. The results conclude that outlier identification and correction must be performed before further assimilation of GRACE products into hydrological or hydro-meteorological analysis. Further, a longrange correlation has been identified as another source of uncertainty in GRACE monthly solutions. EOF analysis is employed to identify the zonal behaviour of the GRACE C20 errors as the responsible source for the long-range correlation. It is considered as an error source because its residual contains tidal aliasing errors instead of white noise. Therefore, to reduce the uncertainties in GRACE monthly solutions, tidal aliasing errors are also investigated. Primary and secondary tidal aliasing errors of main tidal constituents, S1, S2, P1, K1, K2, M2, O2, O1 and Q1 are identified in GRACE monthly solutions. The effect of tidal aliasing error is estimated using a least squares Fourier analysis indicating errors up to 22mm over the globe. In general, after dealing with GRACE’s challenges and achieving a data set without outliers, long-range correlation and tidal aliasing errors, the noise level of GRACE is quantified. The quantification shows a variation between 2–20mm/month over different parts of the globe, with higher values over tropical and boreal regions. The results specifically confirm that small catchments in the tropics contain more noise contamination. It is also shown that a lower noise level of a catchment does not necessarily lead to a better correlation of GRACE with hydro-meteorological signal. Finally, the joint performance of spaceborne geodetic sensors for estimating the actual evapotranspiration ETa is assessed. There, two approaches are introduced to estimate ETa using the results of GRACE and satellite altimetry. The results of both approaches are compared with different models and their ensemble mean. All in all, given the obtained relative discrepancy, the methods seem to be a viable way for determining ETa for most non-desert catchments containing hot and warm summers.Item Open Access Change detection using SAR data(2013) Cao, WenxiThe objective of this thesis is to find changes caused by natural disaster from two co-registered calibrated TerraSAR-X images. Three methods are used in this thesis. The first method, histogram thresholding, uses the histogram of the SAR intensity ratio image to classify the ratio image into three classes. This technique was originally proposed by Kittler et al. (1986) and modified by Bazi et al. (2005) and Moser et al. (2006) based on the Bayesian formula. In this thesis their methods are combined together to detect three classes. The relative difference of the cost function is used to detect the number of the classes instead of the determinant of the Hessian matrix suggested by Bazi et al. (2005). The second method formulates the classification problem as a hypothesis testing problem. This idea was originally used by Touzi et al. (1988) and Oliver et al. (1996). In this thesis the analytical method by Touzi et al. (1988) is replaced by using the properties of the Gamma distribution. The third method, graph-cut algorithm, is a post-processing method, which improves classification results from the first and second methods. The provement is equivalent to the global optimization of an energy function in a Markov random field (MRF). A modern method proposed by Kolmogorov et al. (2004) and Boykov et al. (2004) is used in this thesis. This method transforms the energy function of a MRF into an equivalent graph and solves the global optimization problem using a max-flow/min-cut algorithm. These three methods are applied to the test data on Queensland, Australia, and Leipzig, Germany. Most SAR ratio images can be classified into three classes successfully. The remaining problem is that the interpretation of the changed classes is still ambiguous. Other data sources should be combined to assist or improve the interpretation of the detected change.Item Open Access Least-squares prediction of runoff(2013) Thor, RobinWhen modelling hydrological cycles, the runoff of a drainage basin is an important variable, being an output from hydrological models and an input to many hydrological interactions as a quantity used for validation and calibration. In this context, the decrease of the availability of in situ runoff measurements that has been observed over the last years poses a challenge which this study aims to tackle with the methods of least-squares prediction. This research uses the spatial correlations between in situ runoff measurements generated in a training period to predict values for a validation period during which one of the catchments is assumed ungauged. Different methods include the usage of covariance matrices, which are formed 1. on the signal level, or 2. separately for each of the 12 months of the year, or 3. after the reduction of the monthly mean, or 4. after the reduction of the long-term mean for prediction purposes. For validation, the Nash-Sutcliffe model efficiency coefficient, correlation, and RMSE are computed. The impacts of variations in the length of the training period and of the choice of catchments whose observed measurements are used in the prediction process are analysed. The errors then undergo a spectral analysis to test, which prediction methods are able to capture cyclostationary behaviour best. Most of the methods provide viable results, although the prediction based on covariance matrices generated out of residuals is slightly better than the other methods in a vast majority of configurations. After a training period of 20 years of simultaneous data and with a selection of three catchments used in each prediction process, this method can reach a Nash-Sutcliffe coefficient of over 0.4 for about 90% and of over 0.75 for about 50% of the 25 analysed catchments, although viable results can already be achieved with much shorter training periods of one to three years, depending on the predicted catchment.Item Open Access Coherency analysis between SGs at BFO and Strasbourg(2013) Zhang, YingThe twin satellite GRACE mission has provided high-precision, spaceborne measurements of the Earth time-varying gravity field. Independent validation of the GRACE derived gravity field models using superconducting gravimeters (SGs) has been discussed controversially in the literature, since SGs provide gravity observations at a stationary point with high-precision and low instrumental drift. To evaluate whether ground based gravity observations can be used to validate GRACE gravity field models we compare 3 years of continuous SG data from the Strasbourg Observatory (ST) and the Black Forest Observatory (BFO). These two stations are only 57.5 km apart which is twelve times smaller than the shortest resolved wavelength (about 700 km) in the weekly GRACE gravity field models. Thus, since GRACE derived models predict essentially the same temporal gravity field variations for both ST and BFO we require high correlation between ST and BFO at periods longer than one week. A lack of correlation at these long periods would point to more local sources of these gravity variations and would make a GRACE validation impossible, if BFO and ST are representatives of typical GGP stations. The coherence between the residuals of the two stations ranges from 0.65 to 0.9 at periods from 15 days to 30 days. We further investigate the local hydrology of the SG stations which may not be embodied in the GRACE predictions. Local hydrological signals are known to be a major signal in gravity residuals at period longer than 1 day. We inspect locally recorded precipitation and global hydrological models data in this context. The difference of residuals between the two stations is enlarged after correcting for the local hydrological effects. Correcting for the local hydrological effects using GLDAS model or ERA-interim does not improve the coherence from 15 days to 30 days significantly. The trends of SG residual variations before correcting for local hydrology agree well with GRACE predictions. We suggest more sophisticated measuring and modelling of local hydrology to better estimate the hydrological effect.Item Open Access Sampling the earth's time-variable gravity field from satellite orbit : design of future gravity satellite missions(2013) Iran Pour, Siavash; Sneeuw, Nico (Prof. Dr.-Ing.)The launch of the GRACE mission has generated a broad interest within the geophysical community in the detection of temporal gravity fields and their applications, e.g. the detection of ice mass loss over Greenland and Antarctica, the hydrological cycle over Amazon and central Africa and the estimation of sea level rise. However the spatio-temporal resolution of GRACE solutions is limited by a restricted sensitivity of the metrology system, the reduced isotropy of the inline leader-follower formation (which mainly manifests itself in a North-South striped error pattern) and the temporal aliasing of high frequency time variable geophysical signals into the long time-interval solutions. When using high quality sensors in future gravity missions, aliasing of the high frequency (short period) geophysical signals to the lower frequency (longer period) signals is one of the most challenging obstacles. Two sampling theorems mainly govern the space-time sampling of a satellite-mission: (i) a Heisenberg-type principle in satellite geodesy which states that the product of spatial resolution and time resolution is constant, and (ii) the Colombo-Nyquist rule (CNR), which requires the number of satellite revolutions in the full repeat-cycle to be equal at least twice the maximum spherical harmonic degree to be detected. The latter rule, therefore, limits the spatial resolution of the solution. This study investigates the quality of sub-Nyquist recoveries, i.e. solutions from time intervals shorter than required by CNR, of different orbit configurations and satellite formations. In particular, the dependence of such quality on the measurement duration and ground-track patterns is investigated. It is shown that (i) the number of observations with specific coverage of the Earth by a satellite configuration (as indicated by a modified Colombo-Nyquist rule), (ii) the mission altitude and (iii) avoidance of large unobserved gaps by satellite ground-track patterns have the most important effect on the quality of the recoveries. The sub-cycle concept apparently does not play an important role in assessing the quality. Moreover, the study investigates the modified Colombo-Nyquist rule for two pairs of satellites, where the number of revolutions by both satellite pairs is taken into account. It is also found that sub-Nyquist recoveries by such double pair scenarios outperform the ones from single inline satellite missions with twice the size of time intervals. It is indeed expected that using an inclined satellite mission, together with a near-polar mission, adds East-West measurement component to the North-South component of the near-polar satellite mission. Furthermore, the short time interval recoveries suffer less from temporal aliasing of certain time-variable gravity field components. Consequently, it means that the recovery also benefits from higher time resolution. The gravity recovery simulations of this study are based on a quick-look tool, developed at the Institute of Geodesy, University of Stuttgart. The closed-loop simulation tool assumes a nominal repeat orbit for a satellite mission. Based on the quality assessment of the recoveries and the technical concerns with the implementation of formation flights, a near-polar moderate pendulum formation with an opening angle of less than 10°, approximately 300 km altitude and almost homogeneous gap evolution is suggested for a next generation of single pair gravity mission. For double pair satellite missions, a combination of a near-polar inline or moderate pendulum and a 72° inclined inline pair is recommended. The suggested optimal scenarios of this study are selected through the quality assessment of sub-Nyquist gravity recoveries of different configurations. It is also shown that the quality of the sub-Nyquist gravity recoveries can be improved by employing post processing tools. The post-processing tools of this research study include a white noise filter, based on EOF+KS-Test analysis and a regularization method which can handle all kinds of noise. The tools are employed to deal with the poorer quality of short-time interval recoveries due to the spatial aliasing, although it is almost impossible to remove all noise without diminishing some of the real signals.