Estimating and correcting the penetration bias in interferometric X-band SAR elevation models for the detection of elevation and mass changes of the Greenland ice sheet

• Applicant: Dr. Sahra Abdullahi
• Subject Area: Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography ; Physical Geography
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 457342986

Ongoing global warming leads to dramatic changes of the cryosphere, whereas the Greenland ice sheet in particular has lost considerable mass in the past decades. According to future projections, this trend will intensify and the resulting rise in global sea level will have wide-ranging consequences for humans and the environment. However, the degree of uncertainty is high due to strongly varying data availability and quality on the state and development of the ice sheet. Therefore reliable information is urgently required to improve the forecasting ability and to develop mitigation and adaptation strategies. In this context, spaceborne remote sensing offers a suitable and cost-efficient tool for data collection. Especially single-pass SAR (synthetic aperture radar) interferometry provides considerable advantages due to weather- and illumination-independent as well as area-wide data acquisition with high spatial resolution. The TanDEM-X mission enables for the first time a globally consistent height measurement with a spatial resolution of 0.4 arc seconds. However, the penetration of the radar signals up to several meters below the surface of the ice sheet poses a major challenge when using this elevation data for cryosphere and climate impact research.Against this background, the central goal of the project is the estimation and correction of the penetration bias in interferometric X-band SAR elevation models for precise detection of elevation and mass changes. For this purpose, a generic approach will be developed to correct the TanDEM-X elevation models over the Greenland ice sheet and to derive elevation as well as mass changes of the past decade with high accuracy. The penetration bias will be estimated by means of a pixel-based approach using interferometric coherence and backscatter intensity under consideration of non-linear regression models and neural networks. A homogeneous database of surface heights mainly from laser altimeter data will be the basis for model calibration and validation. Since both the acquisition parameters and the snow and ice characteristics significantly influence the penetration bias, sensitivity analyses with respect to radiometric calibration, acquisition geometry, acquisition time and local topography will be performed to evaluate the impact of the individual parameters on the model accuracy. Beyond the scope of the project, the spatial and temporal transferability of the approach will potentially allow the monitoring of Antarctica, the Arctic ice caps and the glaciated high mountains, as well as an application to future single-pass SAR interferometry missions.

• DFG Programme: Research Grants