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Open AccessArticle

Geocoding Error Correction for InSAR Point Clouds

1
Remote Sensing Technology Institute, German Aerospace Center, 82234 Weßling, Germany
2
Signal Processing in Earth Observation, Technical University of Munich, 80333 Munich, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1523; https://doi.org/10.3390/rs10101523
Received: 14 August 2018 / Revised: 13 September 2018 / Accepted: 20 September 2018 / Published: 22 September 2018
(This article belongs to the Special Issue Imaging Geodesy and Infrastructure Monitoring)
Persistent Scatterer Interferometry (PSI) is an advanced multitemporal InSAR technique that is capable of retrieving the 3D coordinates and the underlying deformation of time-coherent scatterers. Various factors degrade the localization accuracy of PSI point clouds in the geocoding process, which causes problems for interpretation of deformation results and also making it difficult for the point clouds to be compared with or integrated into data from other sensors. In this study, we employ the SAR imaging geodesy method to perform geodetic corrections on SAR timing observations and thus improve the positioning accuracy in the horizontal components. We further utilize geodetic stereo SAR to extract large number of highly precise ground control points (GCP) from SAR images, in order to compensate for the unknown height offset of the PSI point cloud. We demonstrate the applicability of the approach using TerraSAR-X high resolution spotlight images over the city of Berlin, Germany. The corrected results are compared with a reference LiDAR point cloud of Berlin, which confirms the improvement in the geocoding accuracy. View Full-Text
Keywords: geocoding; geodetic corrections; ground control point; persistent scatterer interferometry; positioning; synthetic aperture radar; TerraSAR-X geocoding; geodetic corrections; ground control point; persistent scatterer interferometry; positioning; synthetic aperture radar; TerraSAR-X
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MDPI and ACS Style

Montazeri, S.; Rodríguez González, F.; Zhu, X.X. Geocoding Error Correction for InSAR Point Clouds. Remote Sens. 2018, 10, 1523.

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