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

持续的全球变暖导致冰冻圈的剧烈变化，而格陵兰冰盖在过去几十年中损失了相当大的质量。根据未来的预测，这一趋势将会加剧，由此导致的全球海平面上升将对人类和环境产生广泛的影响。然而，由于关于冰盖状态和发展的可用数据和质量变化很大，不确定性的程度很高。因此，迫切需要可靠的信息来提高预测能力并制定缓解和适应战略。在这方面，星载遥感为数据收集提供了一种适当和具有成本效益的工具。特别是单次SAR（合成孔径雷达）干涉测量技术，由于不受天气和光照的影响，以及高空间分辨率的全区域数据采集，提供了相当大的优势。TanDEM-X任务首次实现了全球一致的高度测量，空间分辨率为0.4角秒。然而，当使用这些海拔高度数据进行冰冻圈和气候影响研究时，雷达信号在冰盖表面以下几米处的穿透构成了一个重大挑战。在此背景下，该项目的中心目标是估算和修正干涉x波段SAR高程模型中的穿透偏差，以精确检测高程和质量变化。为此目的，将开发一种通用方法来校正格陵兰冰盖上的TanDEM-X高程模型，并以高精度得出过去十年的高程和质量变化。在考虑非线性回归模型和神经网络的情况下，采用基于像素的方法，利用干涉相干性和后向散射强度来估计穿透偏置。一个主要来自激光高度计数据的均匀地表高度数据库将成为模型校准和验证的基础。由于采集参数和冰雪特征对穿透偏差都有显著影响，因此将对辐射校准、采集几何形状、采集时间和当地地形进行敏感性分析，以评估单个参数对模型精度的影响。在项目范围之外，该方法的空间和时间可转移性将有可能监测南极洲、北极冰盖和冰川覆盖的高山，并应用于未来的单次SAR干涉测量任务。

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.