The recent legislation Act Nr.4/2011 about Geospatial Information in Indonesia gives exclusive authority to the Geospatial Information Agency of Indonesia (BIG) as the only responsible institution providing the official topographic map of Indonesia. It must cover 1.9 million square kilometers land area of Indonesia which is approximately more than 5 times the land area of Germany. This governmental act opens an opportunity and a challenge for the geospatial data production especially to support the economic development in Indonesia. In that case, the appropriate technologies and methodologies have to be integrated and synchronized to speed up the huge topographic mapping volume in particular for Large Scale Topographic Mapping (LSTM) i.e. equal or larger than 1:10,000. Space borne radar is a reliable technology nowadays to provide base data for topographic mapping. Its flexibility and weather independency make radar data more attractive in comparison with the traditional airborne data acquisition. On the other hand, the Unmanned Aerial Vehicle (UAV) data is also widely used as a potential source to produce high resolution geospatial data. These aforementioned advantages emplace both radar and UAV data as alternative sources for many applications including LSTM. Currently, the available TerraSAR-X add on Digital Elevation Model X (TanDEM-X) Intermediate Digital Elevation Model (IDEM) from German Aerospace Center (DLR) as one useful global scientific data set however still complies with High Resolution Terrain Information (HRTI) level 3 only. The accuracy of the end product of pairwise bi-static TanDEM-X data in a what so called the Interferometric Synthetic Aperture Radar (InSAR) data processing can be improved by some potential measures such as the incorporation of Ground Control Points (GCPs) and Digital Elevation Model (DEM) reference taken from UAV. Therefore it is necessary to find the optimal solution for the InSAR DEM generation with a proper adjustment model. In this dissertation, a new algorithm using both, UAV and TanDEM-X radar data is introduced to process the bi-static TanDEM-X datasets and to investigate how this method improves the accuracy of the generated DEM. As InSAR data processing relies on accurate GCPs and/or DEM reference data, the Indonesian Geospatial Reference System (SRGI) is used as a national framework of the investigations. Subsequently, the DEM generated using the Sentinel Application Platform (SNAP) desktop, is the main product used for LSTM. This DEM has to be assessed using Independent Check Points (ICPs) derived e.g. from conventional airborne data acquisition using metric camera and the accuracy is compared also with the accuracy of the IDEM. Summarized, this dissertation aims on an improvement of LSTM by using UAV and TanDEM-X data e.g. through the introduced linearized model of InSAR data processing.
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