Abstract
Persistent Scatterer Interferometry (PSI) is a powerful radar-based remote sensing technique, able to monitor small displacements by analyzing a temporal stack of coherent synthetic aperture radar images. In an urban environment it is desirable to link the resulting PS points to single buildings and their substructures to allow an integration into building information and monitoring systems. We propose a distance metric that, combined with a dimension reduction, allows a clustering of PS points into local structures which follow a similar deformation behavior over time. Our experiments show that we can extract plausible substructures and their deformation histories on medium sized and large buildings. We present the results of this workflow on a relatively small residential house. Additionally we demonstrate a much larger building with several hundred PS points and dozens of resulting clusters in a web-base platform that allows the investigation of the results in three dimensions.
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Acknowledgements
The SAR data were provided by the German Aerospace Center (DLR) through the proposal LAN0634. We would like to thank the State Office for Spatial Information and Land Development Baden-Württemberg (LGL) for providing citywide ALS/Mesh data and orthophotos.
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5 Appendix
5 Appendix
As supplementary material, we provide an online visualization of the above presented results. We also provide a secondary, much larger building from the same data set. Those visualizations allow an three-dimensional investigation of the achieved results. A colorized ALS point cloud is shown together with the PS points. The clusters are color coded and correspond with the extracted time series on the right hand side.
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Schneider, P.J., Soergel, U. (2021). Clustering Persistent Scatterer Points Based on a Hybrid Distance Metric. In: Bauckhage, C., Gall, J., Schwing, A. (eds) Pattern Recognition. DAGM GCPR 2021. Lecture Notes in Computer Science(), vol 13024. Springer, Cham. https://doi.org/10.1007/978-3-030-92659-5_40
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DOI: https://doi.org/10.1007/978-3-030-92659-5_40
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