On Juni 21, 2010 the still unique TanDEM-X mission was launched and opened a new era in spaceborne radar remote sensing. The first formation flying radar system was built by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second, TerraSAR-X-like satellite TanDEM-X. The resulting large single-pass SAR interferometer features flexible baseline selection enabling the acquisition of highly accurate cross-track interferograms. The primary objective was the generation of a global Digital Elevation Model (DEM) with unprecedented accuracy (12 m horizontal resolution and 2 m relative height accuracy). While the main mission phase for DEM data acquisition has been finished in 2014, the processing of the global TanDEM-X DEM was concluded in September 2016. The final DEM is well within specifications and features an extremely low percentage of void areas. The scientific exploitation of TanDEM-X is not limited to the DEM and the unique capabilities enable numerous secondary mission objectives based on along-track interfero-metry as well as new bistatic and multistatic SAR techniques. Comparisons of the TanDEM-X DEM with SRTM [1] or of multi-temporal TanDEM-X data revealed dramatic changes and the high dynamic in the Earth's topography. It has been therefore decided to acquire data for a global change layer and the so-called change DEM will become available in 2021. Despite being well beyond their design lifetime, both satellites are still fully functional and have enough consumables for several additional years. Therefore, bistatic operations continue with a focus on changes in the cryosphere and biosphere.

This paper presents for the first time a detailed study on information content of X-band single-pass interferometric spaceborne SAR data with respect to snow facies characterization. An approach for classifying different snow facies of the Greenland Ice Sheet by exploiting X-band TanDEM-X interferometric synthetic aperture radar acquisitions is firstly detailed. Large-scale mosaics of radar backscatter and volume correlation factor, derived from quicklook images of the interferometric coherence, represent the starting point for applying an unsupervised classification method based on the c-means fuzzy clustering algorithm. The data was acquired during winter 2010/2011. A partition of four different snow facies was chosen and interpreted using reference melt data, snow density, and in situ measurements. The variations in the stratification and micro-structure of firn, such as the variations of density with depth and the presence of percolation features, are identified as relevant parameters for explaining the significant differences in the observed interferometric signatures among different snow facies. Moreover, a statistical analysis of backscatter and volume correlation factor provided useful parameters for characterizing the snow facies behavior and analyzing their dependency on the acquisition geometry. Finally, knowing the location and characterization of the different snow facies, the two-way X-band penetration depth over the whole Ice Sheet was estimated. The obtained mean values vary from 2.3 m for the outer snow facies up to 4.18 m for the inner one. The presented approach represents a starting point for a long-term monitoring of ice sheet dynamics, by acquiring time-series, and is of high relevance for the design of future SAR missions as well.

Among the several factors that may affect the quality of interferometric synthetic aperture radar (SAR) products, volume decorrelation represents the coherence loss contribution due to the presence of multiple scatterers within a single resolution cell, which results in an increase in the interferometric phase uncertainty. In this letter, we investigate the effects of volume decorrelation on X-band TanDEM-X interferometric data. TanDEM-X is the first bistatic spaceborne SAR mission and provides a unique, global, and manifold interferometric data set to be exploited for a variety of scientific and commercial applications. The main goal of this letter is to provide the scientific community with a characterization of volume decorrelation effects occurring at X-band for different land cover types and acquisition geometries. The potentials of volume decorrelation contribution at X-band for land classification are discussed as well and some application examples are presented.

TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) is an innovative spaceborne bistatic SAR system comprising the twin satellites TerraSAR-X and TanDEM-X (TSX and TDX, respectively). The primary objective of the mission is the generation of a worldwide, timely, and consistent digital elevation model (DEM) in a bistatic synthetic aperture radar (SAR) configuration with unprecedented accuracy. For TanDEM-X and for future spaceborne SAR missions, an increasing volume of onboard data is going to be demanded. This is due to the employment of large bandwidths, high pulse repetition frequencies, and multiple polarizations, which implies inevitably hard requirements in terms of onboard memory and downlink capacity. In this scenario, SAR raw data quantization represents an essential aspect. The data rate employed for the digitization of the recorded radar signal affects both the amount of data to be stored and transmitted to the ground and the quality of the resulting SAR products. In this paper, the impact of quantization on TanDEM-X monostatic and interferometric data is evaluated. Key quantities in estimating interferometric and SAR performance, such as coherence and phase errors, are investigated in detail. Based on the obtained results, an optimization of the resource-allocation strategy for the global DEM acquisition of TanDEM-X is discussed.