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See detailMULTI-GNSS ERROR CHARACTERISTICS AND BENEFITS TO LONG-TERM MONITORING APPLICATIONS IN GEOSCIENCES
Abraha, Kibrom Ebuy UL

Doctoral thesis (2018)

Global Navigation Satellite System (GNSS)-derived position solutions are used for crustal deformations for long-term monitoring studies such as correcting sea-level records for vertical land movements and ... [more ▼]

Global Navigation Satellite System (GNSS)-derived position solutions are used for crustal deformations for long-term monitoring studies such as correcting sea-level records for vertical land movements and to determine present-day surface-mass changes. In all these studies scientists rely heavily on precise International GNSS Service (IGS) products. In recent years the IGS products have partly been generated from a rigorous combination of GNSS, such as Global Positioning System (GPS) and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) observations. Although combined solutions from two or more GNSS benefit from the diversity and redundancy of having more than one GNSS, the solutions are also subjected to system-specific systematic errors. Applications which demand high-accuracy products, therefore, would profit from evaluations of the benefits and error characteristics of combined GNSS solutions. In response to the increased availability of multi-GNSS observations from a truly global ground network of receivers, the goal of this thesis is to investigate their overall impacts on the derived products. Primarily, the impacts of combined GNSS data processing for stations in a constrained environment with a potential for signal obstructions, is investigated. The effects of signal obstructions on derived parameter time series and station velocity estimates are assessed. The benefits of combined solutions are evaluated for stations in constrained environments. Moreover, the study of the impacts of combined solutions on satellite orbits and station parameters contributes to the understanding of the error characteristics of combined GNSS data processing on derived products. The consistency of the parameters, noise analysis and system-specific periodic errors are assessed. Dominant system specific periodic errors and the impact of combined solutions on reducing the effects are addressed. Unmodelled or insufficiently modelled (sub-)daily errors propagate to longer periods and appear in high-end products coinciding with other longer periods, which in turn may lead to misleading interpretations of the latter. The propagation mechanism mainly depends, among other factors, on data sampling deficiencies and GNSS ground repeat periods. Here, the results of this study show that combined solutions not only reduce system-specific effects but also provide a means to identifying the sources from other compatible elements. [less ▲]

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See detailTowards multiscale data fusion of high-resolution space borne and terrestrial datasets over Tristan da Cunha
Backes, Dietmar UL; Teferle, Felix Norman UL; Abraha, Kibrom Ebuy UL et al

Poster (2018, April 10)

Ever improving low cost, lightweight and easy to use sensing technologies are enabling the capture of rich 3D Datasets to support an unprecedented range of applications in Geosciences. Especially low-cost ... [more ▼]

Ever improving low cost, lightweight and easy to use sensing technologies are enabling the capture of rich 3D Datasets to support an unprecedented range of applications in Geosciences. Especially low-cost LiDAR systems as well as optical sensors, which can be deployed from terrestrial or low altitude aerial platforms, allow the collection of large datasets without detailed expert knowledge or training. Dense pointcloud derived from these technologies provide an invaluable source to fill the gap between highly precise and accurate terrestrial topographic surveys and large area Digital Surface Models (DSMs) derived from airborne and spaceborne sensors. However, the collection of reliable 3D pointclouds in remote and hazardous locations remains to be very difficult and costly. Establishing a reliable georeference, ensuring accuracy and data quality as well as merging such rich datasets with existing or space borne mapping provide additional challenges. The presented case study investigates the data quality and integration of a heterogeneous dataset collected over the remote island of Tristan da Cunha. High-resolution 3D pointclouds derived by TLS and drone Photogrammetry are merged with space borne imagery while preserving the accurate georeference provided by Ground Control derived from geodetic observations. The volcanic island of Tristan da Cunha located in the centre of the Southern Atlantic Ocean is one of the most remote and difficult to access locations on the planet. Its remote location, rough climatic conditions and consistent cloud coverage provides exceptional challenges for terrestrial, aerial as well as space borne data acquisition. Amongst many other scientific installations, the island also hosts a continuous GNSS station observation and monitoring facilities operated by the University of Luxembourg, which provided the opportunity to conduct a local terrestrial data acquisition campaign consistent with a terrestrial ground survey, Laserscanning and an image acquisition from a low-cost drone. The highly accurate Ground Control network, observed by GNSS and total station, provides a reliable georeference. Pointclouds were acquired around the area of the harbour using a Leica P20 terrestrial Laserscanner, as well as drone Photogrammetry based on images collected by a low-cost DJI Phantom3 drone. To produce a map of the complete island a comprehensive dataset of high-resolution space borne imagery based on the Digital Globe WorldView constellation was acquired which provided high resolution mapping information. The case study presents a cross-validation of terrestrial, low altitude airborne as well as spaceborne datasets in terms coregistration, absolute georeference, scale, resolution and overall data quality. Following the evaluation a practical approach to fuse this heterogeneous dataset is applied which aims to preserve overall data quality, local resolution and accurate georeference and avoid edge artefacts. The conclusions drawn from our preliminary results provide some good practice advice for similar projects. The final topographic dataset enables mapping and monitoring of local geohazards as, e.g. coastal erosion and recent landslides thus also supporting the local population. [less ▲]

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