Search

This study focuses on deriving methods for a remote sensing based lake/reservoir volume estimation by applying heterogeneous multisensor Earth observation data and global hydrological models. The study estimates gravimetric and geometric variations ongoing in the Aral Sea and the Lake Mead regions. The results demonstrate that lakes/reservoirs can be effectively monitored using remote sensing data., Diese Arbeit beschäftigt sich mit der Entwicklung von Methoden zur Abschätzung des Wasservolumens in Seen und Wasserreservoirs mithilfe multisensoraler Erdbeobachtungsdaten und globaler hydrologischer Modelle. Diese Studie analysiert gravimetrische und geometrische Veränderungen des Aralsees und des Lake Mead. Die Ergebnisse verdeutlichen, dass Seen und Wasserreservoire effektiv mithilfe von Fernerkundungsdaten überwacht werden können

In this study we use CryoSat-2 SAR (delay-Doppler synthetic-aperture radar) data in the Mekong River Basin to estimate water levels. Compared to classical pulse limited radar altimetry, medium- and small-sized inland waters can be observed with CryoSat-2 SAR data with a higher accuracy due to the smaller along track footprint. However, even with this SAR data the estimation of water levels over a medium-sized river (width less than 500 m) is still challenging with only very few consecutive observations over the water. The target identification with land-water masks tends to fail as the river becomes smaller. Therefore, we developed a classification approach to divide the observations into water and land returns based solely on the data. The classification is done with an unsupervised classification algorithm, and it is based on features derived from the SAR and range-integrated power (RIP) waveforms. After the classification, classes representing water and land are identified. Better results are obtained when the Mekong River Basin is divided into different geographical regions: upstream, middle stream, and downstream. The measurements classified as water are used in a next step to estimate water levels for each crossing over a river in the Mekong River network. The resulting water levels are validated and compared to gauge data, Envisat data, and CryoSat-2 water levels derived with a land-water mask. The CryoSat-2 water levels derived with the classification lead to more valid observations with fewer outliers in the upstream region than with a land-water mask (1700 with 2% outliers vs. 1500 with 7% outliers). The median of the annual differences that is used in the validation is in all test regions smaller for the CryoSat-2 classification results than for Envisat or CryoSat-2 land-water mask results (for the entire study area: 0.76 m vs. 0.96 m vs. 0.83 m, respectively). Overall, in the upstream region with small- and medium-sized rivers the classification approach

In this study interrelations between soil moisture and terrestrial water storage are analyzed by using multi-sensor earth observations from satellites and the outputs of a hydrological model. The study targets at a better understanding of the dynamics and drivers of soil moisture and terrestrial water storage on global scale. Another objective is to find out whether the combined analysis of both parameters creates added value for their application in the field of natural disaster monitoring., In dieser Studie wird auf Grundlagen von Erdbeobachtungsdaten von verschiedenen Satellitensensoren und den Daten eines hydrologischen Modells untersucht, welche Zusammenhänge zwischen der Bodenfeuchtigkeit und dem terrestrischen Wasserspeicher bestehen. Ziel der Analyse ist es, auf globaler Ebene ein besseres Verständnis über die Veränderungen der Bodenfeuchtigkeit und des terrestrischen Wasserspeichers zu erlangen. Außerdem sollen die Ergebnisse Aufschluss darüber geben, ob die Verknüpfung beider Parameter einen Mehrwert für ihre Verwendung beim Monitoring von Naturkatastrophen darstellt.

In this thesis, laser ranging observations to satellites (SLR) are used to study correlations of fundamental geodetic parameters such as station coordinates, Earth orientation parameters and coefficients of the Earth’s gravitational field. SLR is used for the investigation since it is highly sensitive to each parameter group through satellite orbit dynamics. The findings of this thesis support the way towards the integrated estimation of the Earth’s geometry, rotation and gravitational field., In dieser Dissertation werden Korrelationen zwischen fundamentalen geodätischen Parametern wie Stationskoordinaten, Erdorientierungsparameter und Koeffizienten des Erdschwerefelds mit Hilfe von Laserentfernungsmessungen zu Satelliten (SLR) untersucht. SLR eignet sich besonders für diese Untersuchung da die Beobachtungen hochsensitiv auf alle Parametergruppen aufgrund der Satellitenbahndynamik sind. Die Erkenntnisse dieser Arbeit liefern einen wichtigen Beitrag auf dem Weg zu einer integrierten Schätzung von Geometrie, Rotation und Schwerefeld der Erde.