The research envisioned in this proposal will lead to a new kind of city models for monitoring and visualization of the dynamics of urban infrastructure in a very high level of detail. The change or deformation of different parts of individual buildings will be accessible for different types of users (geologists, civil engineers, decision makers, etc.) to support city monitoring and management as well as risk assessment.

In this project, the potentials of TerraSAR-X and TandDEM-X missions are fully exploited for an analysis of 3D structures and objects by tomographic SAR methods and PSI in order to by-pass geometrical limitations (such as layover) of radar, and therefore to enhance the precision and quality of TanDEM-X elevation models.

In this project Persistent Scatterer Interferometry is applied to stacks of high resolution TerraSAR-X spotlight data and final positions of PS are estimated in 3D space. With the help of high resolution digital elevation models (DEM), which are generated from airborne laser or optical (stereo) data, the obtained PS can be evaluated with respect to their position on the buildings and therefore the - up to now mostly unknown - nature of the PS can be investigated as soon as the exact positions are known.

For supporting the geometrical interpretation of spaceborne SAR images and results from interferometric SAR methods, a simulation tool, named RaySAR, has been developed. It enables the analysis of reflection effects appearing at urban objects. Highly detailed 3D models of selected man-made objects are illuminated by a virtual SAR sensor in order to simulate the position of radar signals in three dimensions. The main focus of this research project is to identify the origin of salient SAR image signatures on the object, i.e. to provide a link between the SAR image and the geometry of the corresponding object.

In this project, a system for tracking individual vehicles in complex urban environments is developed. The input data is obtained from airborne image sequences using commercial medium format frame cameras. The aim is to monitor large urban environments dealing with complex traffic scenarios to derive area-wide traffic parameters.

The interpretation of multiple trajectories of persons using airborne image sequences is a important field of research with regard to security reasons at big events. So far, only single trajectories have been used for event detection using near-range surveillance cameras. Our goal is to obtain an event detection system by learning meaningful scenarios using Hidden Markov Models with multiple observated features. A dynamic network containing all trajectories within the scene is then used to extract areas where a representative scenario is currently happening.

The project “SafeEarth” is part of the TU München International Graduate School of Science and Engineering (IGSSE), funded by the Excellence Initiative of the German federal and state governments. The project is directed towards the fast, integrated, geometrically and semantically correct interpretation of multi-sensorial airborne and space borne images. The methods will be developed for optical and radar data with the goal to support a fast reaction after natural disasters.