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.

To improve the interpretation of the low density InSAR data a combination is made with high density airborne and terrestrial laser scanner data. Allowing for improvement of the positioning of the scatterers and the understanding of their behaviour. This combination is implemented as a web application, suitable for researchers to create 3D visualisations for the greater public. Results of this work are a demo application, this report and a manual on how to make a similar application based on a combination of yet existing tools