Volume XLII-2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1137-1144, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-1137-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 1137-1144, 2018
https://doi.org/10.5194/isprs-archives-XLII-2-1137-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 May 2018

30 May 2018

MASSIVE LINKING OF PS-INSAR DEFORMATIONS TO A NATIONAL AIRBORNE LASER POINT CLOUD

A. L. van Natijne, R. C. Lindenbergh, and R. F. Hanssen A. L. van Natijne et al.
  • Delft University of Technology, Department of Geoscience and Remote Sensing, Stevinweg 1, 2628CN Delft, The Netherlands

Keywords: Airborne Laser Scanning, PS-InSAR, geolocation, deformation monitoring, local surface reconstruction, data fusion

Abstract. Build on soft soil, close to sea level the Netherlands is at high risk for the effects of subsidence and 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 position accuracy of this LiDAR point cloud is to low for deformation estimates, linking the InSAR location to the geometries outlined by the LiDAR point can improve the geolocation estimates of the InSAR trends. To our knowledge no such integration is available as of yet. In this article we outline methods to link deformation estimates to the LiDAR point cloud and give an outlook of possible improvements. As a test we link 3.1 million TerraSAR-X InSAR Persistent Scatterers to 3 billion LiDAR points, covering the city of Delft and surroundings.