ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 157–163, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-157-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 157–163, 2020
https://doi.org/10.5194/isprs-annals-V-3-2020-157-2020

  03 Aug 2020

03 Aug 2020

EXTRACTING AND EVALUATING CLUSTERS IN DINSAR DEFORMATION DATA ON SINGLE BUILDINGS

P. J. Schneider1, R. Khamis2, and U. Soergel1 P. J. Schneider et al.
  • 1Institute for Photogrammetry (ifp), University of Stuttgart, Germany
  • 2Deutsche Bahn AG, Germany

Keywords: Persistent Scatterer Interferometry (PSI), Urban Deformation Monitoring, Time Series Analysis, Data Mining

Abstract. In the past two decades persistent scatterer interferometry (PSI) has become a well understood and powerful method to monitor the deformations of man-made structures. PSI can derive displacement histories of thousands of scattered points on a single building with accuracy of a few millimetre per year, by analysing space-borne SAR data. In this paper, we present a method to cluster PS points on a single building into segments which show the same deformation behavior. The spatial distribution of those clusters gives an insight into the structural behavior of a building. We use dimensionality reduction to visualize the clusters in the deformation space. The comparison of our extracted displacement patterns with ground truth data from precise levelling and 3D tachymetry confirms the plausibility of our remote sensing method.