Preprints
https://doi.org/10.5194/egusphere-2025-3998
https://doi.org/10.5194/egusphere-2025-3998
10 Oct 2025
 | 10 Oct 2025
Status: this preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).

One-day repeat pass interferometry highlights the role of temporal baseline on digital elevation models retrieved from Sentinel-1

Andreas Braun

Abstract. Digital Elevation Models (DEMs) derived from Synthetic Aperture Radar (SAR) interferometry are a key data source for numerous geospatial applications, from hydrological modelling to environmental monitoring. The launch of Sentinel-1C in late 2025 introduces a new sensor into the Sentinel-1 constellation. This study evaluates the vertical accuracy of DEMs generated from interferometric image pairs acquired during the satellite’s calibration phase. The analysis uses a set of image pairs with temporal baselines of 1, 6, and 12 days, over a test site in Angola, validated against ICESat-2 elevation measurements. The workflow includes interferometric processing, coherence assessment, and statistical error evaluation. Results indicate high accuracy for the 1-day pair (RMSE ≈ 14.7 m) and moderate degradation for the 6-day pair (RMSE ≈ 16.4 m), but a pronounced loss of accuracy for the 12-day pair (RMSE ≈ 49.4 m), primarily linked to coherence loss in vegetated areas. Coherence and elevation error distributions reveal clear land cover and slope dependencies, with lower performance in forested and steep terrain. These findings should be regarded as indicative due to the limited number of suitable image pairs for the calibration phase. However, this early assessment provides an important reference point for future Sentinel-1A/C DEM generation studies, informing both methodological refinement and application planning in SAR-based topographic mapping.

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Andreas Braun

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Andreas Braun
Andreas Braun

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Short summary
The study examines how new satellite images can be used to create detailed maps of Earth’s surface height. Analysis of Sentinel-1C data shows that very short time gaps between images produce the most accurate results, while longer gaps reduce quality, especially over forests and steep terrain. The findings provide guidance for improving future mapping and environmental monitoring from space.
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