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Research topics

Information retrieval from remote sensing data

We develop explorative algorithms to improve information retrieval from remote sensing data, in particular those from current and the next generation of Earth observation missions such as TerraSAR-X, TanDEM-X, TerraSAR-X follow-on, Tandem-L and EnMAP. For instance, for Tomographic SAR inversion, a super-resolution factor of up to 25 has been achieved by using compressive sensing techniques.

City mapping

New methods to investigate how cities grow will also be in focus. One of the challenges is the creation of high-resolution images suitable for the detection of natural hazards and the mapping of cities. For the first time, this information is also combined with data from social networks: Crowdsourcing platforms such as OpenStreetMap provide up-to-date map material; photos posted to the network provide authentic and current images in which buildings can be seen or which, e.g., reveal the extent of damage caused by a flood. The major challenge here is consolidating this information and evaluating it automatically using ML methods.