21 Nov 2023
 | 21 Nov 2023
Status: this preprint is open for discussion.

A new tool for the estimation of Ground-Based InSAR acquisition characteristics before starting installation and monitoring survey

Charlotte Wolff, Marc-Henri Derron, Carlo Rivolta, and Michel Jaboyedoff

Abstract. Synthetic Aperture Radar (SAR) acquisition can be performed from satellites or from the ground by means of a so-called GB-InSAR (Ground-Based Interferometry SAR), but the signal emission and the output image geometry slightly differ between the two acquisition modes. Those differences are rarely mentioned in the literature. This paper proposes to compare satellite and GB-InSAR in terms of (1) acquisition characteristics and parameters to consider; (2) SAR image resolution; (3) geometric distortions that are foreshortening, layover and shadowing.

If in the case of satellites SAR, the range and azimuth resolutions are known and constant along the orbit path, in the case of GB-InSAR their values are terrain-dependent. It is worth estimating the results of a GB-InSAR acquisition one can expect in terms of range and azimuth resolution, Line of Sight (LoS) distance and geometric distortions to select the best installation location when several are possible. We developed a tool which estimates those parameters from a Digital Elevation Model (DEM), knowing the GB-InSAR and the Slope of Interest (SoI) coordinates. This tool, written in MATLAB, was tested on a simple synthetic point cloud representing a cliff with a progressive slope angle to highlight the influence of the SoI geometry on the acquisition characteristics and on two real cases; cliffs located in Switzerland, one in the Ticino canton and on in the Vaud canton.

Charlotte Wolff et al.

Status: open (until 13 Jan 2024)

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Charlotte Wolff et al.

Charlotte Wolff et al.


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Short summary
InSAR is vital for monitoring slope instabilities but requires understanding. This paper delves into differences between satellite and GB-InSAR, addressing geometry and acquisition. It offers a user-friendly tool to determine the best GB-InSAR installation location, considering various technical, meteorological, and topographical factors, streamlining the campaign setup.