InSAR Processing Pipeline for Norway - Sleiman Project

This pipeline is a Python-based Jupyter Notebook integration built to track slow-moving ground surface changes using InSAR (Interferometric Synthetic Aperture Radar) data from the InSAR Norway platform. The workflow includes automated data downloading, spatial filtering, calibration, and slope-parallel velocity (Vslope) analysis for landslide and ground deformation monitoring. This pipeline is an adapted version (Sleiman, 2026, in prep.) of a GUI system originally developed in collaboration with Gökhan Aslan at the Geological Survey of Norway (Aslan, 2026, in prep.). This project was partially funded by an EarthCube DeCODER mini grant (https://www.earthcube.org/decoder). DeCODER-indexed platforms were evaluated for all data inputs. OpenTopography was assessed for terrain data, but the available European DTM (30 m resolution) was too coarse to resolve individual solifluction lobes. High-resolution 5 m and 10 m terrain data was sourced from the Norwegian Mapping Authority (Kartverket) and resampled to match analysis needs. The Alaska Satellite Facility (ASF), an EarthCube-affiliated platform, was evaluated for InSAR data but does not currently offer Persistent Scatterer point products needed to detect millimeter-scale solifluction motions. PS-InSAR velocity products were obtained from the Geological Survey of Norway (NGU) through the InSAR Norway service, then reanalyzed and filtered using the resampled terrain data. Processed terrain products are being contributed back to OpenTopography for future use. All code, processed data, and documentation are archived here on Zenodo. The accompanying manuscript was submitted to The Cryosphere, an open-access journal. By depositing research products into DeCODER-indexed platforms, this project extends the discoverability of periglacial InSAR datasets through the science-on-schema framework.