Birgit Wessel

TanDEM-X: The New Global DEM Takes Shape

TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative formation flying radar mission that opens a new era in spaceborne radar remote sensing. The primary objective is the acquisition of a global Digital Elevation Model (DEM) with unprecedented accuracy (12 m horizontal resolution and 2 m relative height accuracy). This goal is achieved by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second, TerraSAR-X like satellite TanDEM-X (TDX) flying in close formation with TerraSAR-X (TSX). The resulting large single-pass SAR interferometer features flexible baseline selection enabling the acquisition of highly accurate cross-track interferograms not impacted by temporal decorrelation and atmospheric disturbances. Beyond the global DEM, several secondary mission objectives based on alongtrack interferometry as well as new bistatic and multistatic SAR techniques have been defined. Since 2010 both satellites have been operated in close formation to map all land surfaces at least twice and difficult terrain even up to four times. While data acquisition for DEM generation will be concluded in the second half of 2014 it is expected to complete the processing of the global DEM by the end of 2015. This paper provides an overview of the TanDEM-X mission and summarizes its actual status as well as the performance of the system and the first final DEMs. Up to now the mission driver was the DEM generation and scientific experiments have been limited to the pre-defined DEM formation geometries. This paper also outlines the current planning for a dedicated science phase starting in the last quarter of this year.

Ensuring globally the TanDEM-X height accuracy: Analysis of the reference data sets ICESat, SRTM and KGPS-tracks

The TanDEM-X mission will derive a global digital elevation model (DEM) with satellite SAR interferometry. Height references play an important role to ensure the required height accuracy of 10m absolute and 2m relative for 90% of the data. In this paper the main height reference data sets ICESat (for DEM calibration), SRTM (for phase unwrapping) and kinematic GPS-Tracks (KGPS — for DEM verification) are analyzed regarding to their accuracy. For the ICESat data a reliable quality measure is developed. For SRTM an improved version adjusted to reliable ICESat data is presented and a concept for collecting and evaluating decimeter-precise kinematic GPS tracks is proposed.

TanDEM-X Water Indication Mask: Generation and First Evaluation Results

The German SAR interferometry mission TanDEM-X performed on two TerraSAR-X satellites flying in close formation will provide a global Digital Elevation Model (DEM). A by-product is so-called the Water Indication Mask (WAM). The purpose of this supplementary information layer is to support the DEM editing process. Water surfaces usually show lower coherence in an interferometric data set due to temporal de-correlation and low backscattering. Consequently the corresponding elevation values derived from the interferogram are random and produce a virtual relief. This paper introduces the operational water body detection workflow that synergistically evaluates amplitude and coherence information. The presented results of two test sites reveal that the methodology is globally applicable, classifications are highly accurate and the algorithm is appropriate for operational image processing. The water body detection consists of two steps: the Water Body Detection (WBD) derived of one single DEM scene and the mosaicking of multiple WBD to a single Water Indication Mask (WAM). The fusion strategy for the final TanDEM-X WAM considers all WBD acquired at different times in two global coverages and bases on a fusion by union containing the results of the amplitude and the coherence.

The TanDEM-X DEM Mosaicking: Fusion of Multiple Acquisitions Using InSAR Quality Parameters

Since 2010, TanDEM-X and its twin satellite TerraSAR-X fly in a close orbit formation and form a single-pass synthetic aperture radar (SAR) interferometer. The formation was established to acquire a global high-precision digital elevation model (DEM) using SAR interferometry (InSAR). In order to achieve the required height accuracy of the TanDEM-X DEM, at least two global coverages have to be acquired. However, in difficult and mountainous terrain, up to five coverages are present. Here, acquisitions from ascending and descending orbits are needed to fill gaps and to overcome geometric limitations. Therefore, a strategy to properly combine the available height estimates is mandatory. The objective of this paper is the presentation of the operational TanDEM-X DEM mosaicking approach. In general, multiple InSAR DEM heights are combined by means of a weighted average with the height error as weight. Apart from this widely used mosaicking approach, one big challenge remains with the handling of larger height discrepancies between the input data, which are mainly caused by phase unwrapping errors, but also by temporal changes between acquisitions. In the case of inconsistencies, the TanDEM-X mosaicking approach performs a grouping into height levels. A priority concept is set up to evaluate the different groups of heights considering the number of DEMs and several InSAR quality parameters: the height error, the phase unwrapping method, and the height of ambiguity. This allows the identification of the most reliable height level for mosaicking. This fusion concept is verified on different test areas affected by phase unwrapping errors in flat and mountainous terrain as well as by height discrepancies in forests. The results show that the quality of the final TanDEM-X DEM mosaic benefits a lot from this mosaicking approach.

An Innovative Curvelet-only-Based Approach for Automated Change Detection in Multi-Temporal SAR Imagery

This paper presents a novel approach for automated image comparison and robust change detection from noisy imagery, such as synthetic aperture radar (SAR) amplitude images. Instead of comparing pixel values and/or pre-classified features this approach clearly highlights structural changes without any preceding segmentation or classification step. The crucial point is the use of the Curvelet transform in order to express the image as composition of several structures instead of numerous individual pixels. Differentiating these structures and weighting their impact according to the image statistics produces a smooth, but detail-preserved change image. The Curvelet-based approach is validated by the standard technique for SAR change detection, the log-ratio with and without additional gamma maximum-a-posteriori (GMAP) speckle filtering, and by the results of human interpreters. The validation proves that the new technique can easily compete with these automated as well as visual interpretation techniques. Finally, a sequence of TerraSAR-X High Resolution Spotlight images of a factory building construction site near Ludwigshafen (Germany) is processed in order to identify single construction stages by the time of the (dis-)appearance of certain objects. Hence, the complete construction monitoring of the whole building and its surroundings becomes feasible.

Curvelet-based Change Detection on SAR Images for Natural Disaster Mapping

This paper focuses on the use of SAR data in the context of natural disasters. A Curvelet-based change detection algorithm is presented that automatically extracts changes in the radar back-scattering from two TerraSAR-X acquisitions – pre-disaster and post-disaster - of the same area. After a logarithmic scaling of the geocoded amplitude images the Curvelet-transform is applied. The differ-entiation is then done in the Curvelet-coefficient domain where each coefficient represents the strength of a linear structure apparent in the original image. In order to reduce noise the resulting coefficient differences are weighted by a special function that suppresses minor, noise-like structures. The resulting enhanced coefficients are transformed back to the image domain and brought to the original scaling, so that the values in the difference image describe the increase and the decrease with respect to the amplitude value in the initial image. This approach is applied on three sample data sets: flood, forest fire, and earthquake. For all scenarios including natural landscapes and urban environ-ments as well areas with changes in the radar amplitude are clearly delineated. The interpretation of the changes detected in the radar images needs additional knowledge, e.g. pre-disaster maps. The combination of both could possibly deliver a robust and reliable database for the coordination of res-cue teams after large-scale natural disasters.

Validation of tie-point concepts by the DEM adjustment approach of TanDEM-X

The aimed accuracies for the final TanDEM-X DEM of 10m absolute and 2m relative height error will be ensured by calibration data. One crucial data set for the relative accuracy is tie-points that connect adjacent DEM acquisitions in the approximately 4km-overlap-area with each other. In this paper an improved concept for tie-point candidates is presented that is based on averaging a larger region instead of comparing single points. This concept should be more robust against noise. It is validated by applying the DEM calibration on a simulated test area, as real TanDEM-X data was not yet available. Also, the DEM calibration will be validated for the first time on a larger “real” test site by applying the TanDEM-X processing scenario.

The role of context for road extraction from SAR imagery

This paper deals with automatic road extraction from airborne SAR imagery. Automatic extracted road networks are often incomplete. Even sophisticated road extraction approaches that are developed for optical imagery often fail to extract a complete road network. In SAR imagery in contrary to optical imagery, roads are more affected by high backscattering context objects. These local context objects like trees, bridges, or vehicles can disturb road extraction, but they can also support it. We show that an explicit modeling of context objects, leads to improved extraction results.

Validation of the absolute height accuracy of TanDEM-X DEM for moderate terrain

In September 2013 the production of TanDEM-X digital elevation model (DEM) started. As the data acquisition for difficult terrain lasted until April 2014, final DEM production started for flat to moderate terrain regions where two final coverages surfice. This paper focuses on a first validation of moderate terrain to prove the absolute height accuracy. In a detailed comparison three DEM tiles from different continents are chosen to validate the TanDEM-X DEM by computing differences to GPS tracks, ICESat validation points, and SRTM. On a global scale all TanDEM-X DEMs produced so far are compared with ICESat and GPS tracks. Both validations presented here for the first time indicate that the absolute height error for moderate terrain for TanDEM-X is below 2m and therefore much better than the specified 10m/LE90.

Production chain towards first calibrated and mosaicked TanDEM-X DEMs

The main product of the TanDEM-X mission is an interferometric DEM product that is finally calibrated due to residual systematic offsets and tilts and where different, generally two coverages, are mosaicked. Above this, a water mask is provided to support later editing of rough water areas. In this presentation the commissioning phase work to set the DEM production chain into operation is described and the first commissioning phase products are shown.