Work

RIPPL, a Python-based InSAR stack and tropospheric delay software package

Year: 2025

Type: article

Abstract: Interferometric Synthetic Aperture Radar (InSAR) has a wide range of applications, including the monitoring of solid-earth and cryospheric geophysical processes and the monitoring of the built environment. The use of InSAR for atmospheric applications is less thoroughly developed. To perform such analyses the atmospheric phase delay of the SAR signal between different overpasses is used, which needs to be disentangled from other phase constituents, such as displacements and topography, which requires stack processing of large data volumes. Typically, initial atmospheric delays are predicted using existing numerical weather prediction (NWP) models, but InSAR processing and NWP model delay estimation software are not well integrated. Here we present a pure Python-based software package that integrates the automatic downloading and processing of InSAR and NWP model data to create time-series of unwrapped InSAR interferograms and InSAR equivalent tropospheric delays from NWP models. By combining the geometry of the InSAR radar signals with different NWP model datasets the tropospheric delays can accurately be derived on a pixel by pixel basis.

Source: Computers & Geosciences

DOI: 10.1016/j.cageo.2025.106069

Authors: G. Mulder, F.J. van Leijen, P. Lopez-Dekker, R.F. Hanssen

Institution: Delft University of Technology

Language: English

Topic: Synthetic Aperture Radar (SAR) Applications and Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,010

Funder: Nederlandse Organisatie voor Wetenschappelijk Onderzoek