Locating PS-InSAR derived deformation using LiDAR point clouds

Master Thesis (2018)
Author(s)

A.L. van Natijne (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

R.F. Hanssen – Mentor

R. C. Lindenbergh – Mentor

P.J.M. Van Oosterom – Mentor

Faculty
Civil Engineering & Geosciences
Copyright
© 2018 Adriaan van Natijne
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Adriaan van Natijne
Graduation Date
27-08-2018
Awarding Institution
Delft University of Technology
Related content

Supplementary materials and live demonstration.

https://dev.fwrite.org/radar/
Faculty
Civil Engineering & Geosciences
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Abstract

Built mainly on soft soil, the Netherlands is at high risk for the effects of deformation. Interferometric Synthetic Aperture Radar (InSAR) is successfully used to monitor the deformation trends at millimetre level. Unfortunately the InSAR deformation trends suffer from poor geolocation estimates, limiting the ability to link deformation behaviour to objects, such as buildings, streets or bridges.
A nationwide, high resolution, airborne LiDAR point cloud is available in the Netherlands. Although the LiDAR point
cloud itself is unsuitable for deformation estimates, linking the InSAR location to the geometries outlined by the LiDAR point cloud can improve the geolocation estimates of the InSAR trends.
In this thesis three methods are shown to link deformation estimates to the LiDAR point cloud or reconstructed features thereof. As a test, 3.1 million TerraSAR-X InSAR Persistent Scatterers are linked to 3 billion LiDAR points, covering the city of Delft and surroundings. 85% of the scatterers could be linked to the point cloud. Furthermore an outlook at the possibilities of an implementation on a national scale using Sentinel 1 data is given.

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