6.08 4D City – Space-time Urban Infrastructure Mapping by Multi-sensor Fusion and Visualization

Research

Static 3D city models are well established for many applications such as architecture, urban planning, navigation, tourism, and disaster management. The recent launches of very high resolution (VHR) Synthetic Aperture Radar (SAR) Earth observation satellites, like the German TerraSAR-X, provide for the first time the possibility to derive both shape and deformation parameters of urban infrastructure on a continuous basis. The proposal “4D City” is directed towards 4D (space-time) urban infrastructure monitoring and visualization by fusion of multiple sensors: Differential Tomographic SAR (D-TomoSAR), stereo-optical images and LiDAR (Light Detection and Ranging). The different sensors complement to each other: stereo-optical data have the best visual interpretability, LiDAR provides very accurate Digital Elevation Models (DEM), and D-TomoSAR as well as the related Persistent Scatterer Interferometry (PSI) are the only methods to provide the dynamic component of buildings with up to millimeter accuracy, e.g. seasonal thermal dilation, structural deformation, or subsidence due to groundwater extraction or underground construction.

Since VHR D-TomoSAR of urban infrastructure is a new research area, the development and improvement of appropriate robust TomoSAR algorithms will be the first focus of the project. Second, data fusion for combining the strengths of different sensors will be developed both on the geodetic and the semantic levels. Finally, a particular challenge will be the user specific visualization of the 4D multi-sensor data showing the urban objects and their dynamic behavior. Visualization must handle spatially anisotropic data uncertainties and possibly incomplete dynamic information. It may also integrate some of the data fusion steps. Different levels of user expertise must be considered.

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.

Publications

Shahzad, M., Zhu, X.: "Automatic detection and reconstruction of 2D/3D building shapes from spaceborne TomoSAR point clouds." 2016.

Ding, L., Fan, H., Meng, L.: "Understanding Taxi Driving Behaviors from Movement Data." 2015.

Lyu, H., Ding, L.: "A Mesh-based Free Space Routing Solution". Augsburg, 2015.

Fan, H., Ding, L.: "Can FCD data indicate problems in urban planning? A case study in Shanghai". Augsburg, 2015.

Schmitt, M., Shahzad, M., Zhu, X.: "Reconstruction of individual trees from multi-aspect TomoSAR data." 2015.

"Zhu, X., Ge, N., Shahzad, M.: "Joint Sparsity in SAR Tomography for Urban Mapping." 2015.

Shahzad, M., Zhu, X.: "Robust Reconstruction of Building Facades for Large Areas Using Spaceborne TomoSAR Point Clouds", 2014.

Zhu X., Shahzad, M.: "Facade Reconstruction Using Multiview Spaceborne TomoSAR Point Clouds", 2014.

Wang Y., Zhu X., Bamler R.: "An efficient tomographic inversion approach for urban mapping using meter resolution SAR image stacks", 2013.

Shahzad, M., Zhu, X.: "Robust building façades reconstruction from spaceborne TomoSAR points". Antalya, 2013.  

Shahzad, M., Zhu, X.: "Building Façades Reconstruction Using Multi-View TomoSAR Point Clouds". Sao Paulo, 2013.

Wang, Y., Zhu, X., Bamler, R.: "Integration of tomographic SAR inversion and PSI for operational use."2012.

Wang, Y., Zhu, X., Bamler, R.: "Operational TomoSAR processing using TerraSAR-X high-resolution spotlight stacks from multiple view angles." 2012.

Wang, Y., Zhu, X., Bamler, R.: "Retrieval of Phase History Parameters from Distributed Scatterers in Urban areas using very high resolution SAR data."2012.

Ding, L., Meng, L.: "A comparative study of thematic mapping and scientific visualization", 2012.

Zhu, X., Shahzad, M., Bamler, R.: "From TomoSAR Point Clouds to Objects: Façade Reconstruction". Naples, 2012.

Zhu, X., Bamler, R.: "Let's Do the Time Warp: Multicomponent Nonlinear Motion Estimation in Differential SAR Tomography." 2011.

Wang, Y., Zhu, X., Bamler, R.: "Advanced coherence stacking technique using high resolution TerraSAR-X spotlight data." 2011.

Wang, Y., Zhu, X., Bamler, R.: "Optimal estimation of distributed scatterer phase history parameters from meter-resolution SAR data." 2011.

Zhu, X., Bamler, R.: "Tomographic SAR Inversion by L1-Norm Regularization - The Compressive Sensing Approach ", 2010.

Ding, L., Yang, J., Meng, L.: "Visual Analytics for Understanding Traffic Flows of Transport Hubs from Movement Data". Rio de Janeiro, 2010.

Zhu, X., Bamler, R.: "Very High Resolution Spaceborne SAR Tomography in Urban Environment", 2010.

Zhu, X., Adam, N., Bamler, R.: "Space-Borne High Resolution Tomographic Interferometry". Cape Town, 2009.

Zhu, X., et al.: "First demonstration of space-borne high resolution SAR tomography in urban environment using TerraSAR-X data", 2008.

Team

Project team leader

Professor Xiaoxiang Zhu
Assistant Professorship of Signal Processing in Earth Observation

Alumna

Dr.-Ing. Linfang Ding
Chair of Cartography

Doctoral researcher

Lianhuan Wei

Principal investigator

Professor Mingsheng Liao
Wuhan University, China

Principal investigator

Professor Richard Bamler
Chair of Remote Sensing Technology

Principal investigator

Dr.-Ing. Timo Balz
Wuhan University, China