Scatterer identification and analysis using combined InSAR and laser data

Ramon Hanssen, Adriaan van Natijne, Roderik Lindenbergh, Prabu Dheenathayalan, Mengshi Yang, Ling Chang, Freek van Leijen, Paco Lopez Dekker, Jippe van der Maaden, P.J.M. van Oosterom, Hanjiang Xiong, PingBo Hu, Zhang Zhan, Bisheng Yang

Research output: Contribution to journalMeeting AbstractScientific


The geolocation of coherent radar scatterers, used for InSAR deformation analysis, is often not accurate enough to associate them to physical geo-objects. The imaging geometry of satellite InSAR results in (i) biases in the entire point field, and (ii) quite elongated and skewed confidence ellipsoids in the range, azimuth and cross-range direction. The metric defined by the covariance matrix of the InSAR results defines the optimal way to associate scatterers with geo-objects. Laser scanning point clouds, stemming from aerial or terrestrial laser surveys, yield very dense geometry of geo-objects and topography. Here we combine InSAR and laser point clouds, taking the covariance metrics of the InSAR data into account. This enables us to correct the positions of InSAR data, to provide a geometric match with geo-objects. We demonstrate how this allows for adding contextual information as attributes to individual scatterers, which improves the interpretation of the InSAR results.
Original languageEnglish
Article numberEGU2018-17008
Number of pages1
JournalGeophysical Research Abstracts (online)
Publication statusPublished - 2018
EventEGU General Assembly 2018 - Vienna, Austria
Duration: 8 Apr 201813 Apr 2018


Dive into the research topics of 'Scatterer identification and analysis using combined InSAR and laser data'. Together they form a unique fingerprint.

Cite this