Abstract
Abstract. Synthetic aperture radar interferometry (InSAR) has been an established method for long term large area monitoring. Since the launch of meter-resolution spaceborne SAR sensors, the InSAR community has shown that even individual buildings can be monitored in high level of detail. However, the current deformation analysis still remains at a primitive stage of pixel-wise motion parameter inversion and manual identification of the regions of interest. We are aiming at developing an automatic urban infrastructure monitoring approach by combining InSAR and the semantics derived from optical images, so that the deformation analysis can be done systematically in the semantic/object level. This paper explains how we transfer the semantic meaning derived from optical image to the InSAR point clouds, and hence different semantic classes in the InSAR point cloud can be automatically extracted and monitored. Examples on bridges and railway monitoring are demonstrated.
Highlights
We are aiming at developing an automatic urban infrastructure monitoring approach by combining InSAR and the semantics derived from optical images, so that the deformation analysis can be done systematically in the semantic/object level
Long term deformation monitoring over large area is so far only achievable through differential SAR interferometry (InSAR) techniques such as persistent scatterer interferometry (PSI) (Adam et al, 2003; Ferretti, Prati & Rocca, 2001; Gernhardt & Bamler, 2012; Kampes, 2006) and differential SAR tomography (TomoSAR) (Fornaro et al, 2015; Fornaro, Reale & Serafino, 2009; Lombardini, 2005; Zhu & Bamler, 2010a; Zhu & Bamler, 2010b)
The semantic classification of the InSAR point cloud is achieved by co-registering the InSAR point cloud and an optical image to a common reference 3-D model, so that the semantic classification in the optical image can be transferred to the InSAR point cloud
Summary
Long term deformation monitoring over large area is so far only achievable through differential SAR interferometry (InSAR) techniques such as persistent scatterer interferometry (PSI) (Adam et al, 2003; Ferretti, Prati & Rocca, 2001; Gernhardt & Bamler, 2012; Kampes, 2006) and differential SAR tomography (TomoSAR) (Fornaro et al, 2015; Fornaro, Reale & Serafino, 2009; Lombardini, 2005; Zhu & Bamler, 2010a; Zhu & Bamler, 2010b). The focus of development in differential InSAR techniques has always been on the estimation of the phase history parameters (elevation, motion parameters, etc.) under different scattering models including single deterministic scattering (persistent scatterer), distributed scattering (distributed scatterer), and layover of multiple scatterings (TomoSAR). With meter-resolution SAR data, it is demonstrated that even individual building could be monitored in very high level of detail from space
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