Birgit Wessel

German Aerospace Center (DLR), Köln, North Rhine-Westphalia, Germany

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Publications (42)9.39 Total impact

  • Source
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    ABSTRACT: Abstract-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.
    Geoscience and Remote Sensing Magazine, IEEE. 06/2014; 2(2):8-23.
  • Andreas Schmitt, Birgit Wessel, Achim Roth
    02/2014; 6(3).
  • Andreas Schmitt, Birgit Wessel, Achim Roth
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    ABSTRACT: This paper presents a novel approach for automated image comparison and robust change detection from noisy imagery like SAR amplitude images. In contrast to many other studies which focus either on laminar changes of distributed targets or on changed features this approach clearly points out structural changes without any 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 a carpet of numerous individual pixels. These structures are subsequently compared by differentiating the Curvelet coefficients. The resulting difference image is reduced to considerable, but continuous changes by applying a special weighting function whose parameters are automatically adapted to the coefficients statistics and thus, the image content. As common techniques often overestimate changes the results are validated using are manual reference produced by five SAR experts. It is shown that the automated approach is as reliable as a human interpreter while performing sixty times faster. Finally, the new technique is applied to a sequence of TerraSAR-X High Resolution Spotlight Images the construction site of a factory building near Ludwigshafen (Germany). The Curvelet-based change analysis approach enables the detection of single construction stages by the time of the (dis-)appearance of certain objects and therefore, the complete construction monitoring of the whole building and its surroundings. With regard to multi-polarized SAR acquisitions this technique may be applied to the output layers of polarimetric decompositions for a more detailed change characterization in future.
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 01/2013; · 2.87 Impact Factor
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    ABSTRACT: In June 2010, the German TanDEM-X satellite was launched. Together with its twin satellite TerraSAR-X it flies in a close formation enabling single-pass SAR interferometry. The primary goal of the TanDEM-X mission is the derivation of a global digital elevation model (DEM) with unprecedented global accuracies of 10 m in absolute and 2 m in relative height. A significant calibration effort is required to achieve this high quality world-wide. In spite of an intensive instrument calibration and a highly accurate orbit and baseline determination, some systematic height errors like offsets and tilts in the order of some meters remain in the interferometric DEMs and have to be determined and removed during the TanDEM-X DEM calibration. The objective of this article is the presentation of an approach for the estimation of correction parameters for remaining systematic height errors applicable to interferometric height models. The approach is based on a least-squares block adjustment using the elevation of ICESat GLA 14 data as ground control points and connecting points of adjacent, overlapping DEMs as tie-points. In the first part its implementation in DLR’s ground segment is outlined. In the second part the approach is applied and validated for two of the first TanDEM-X DEM test sites. Therefore, independent reference data, in particular high resolution reference DEMs and GPS tracks, are used. The results show that the absolute height errors of the TanDEM-X DEM are small in these cases, mostly in the order of 1–2 m. An additional benefit of the proposed block adjustment method is that it improves the relative accuracy of adjacent DEMs.
    ISPRS Journal of Photogrammetry and Remote Sensing 09/2012; 73:39–49. · 2.90 Impact Factor
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    ABSTRACT: The main goal of the TanDEM-X mission is the production of a global Digital Elevation Model (DEM). A byproduct is the so-called Water Indication Mask (WAM). The purpose of this supplementary information layer is to support the DEM editing process where the DEM is noisy. The WAM is derived from the SAR amplitude and the single-pass coherence. In this paper, the methodology of the water body detection is briefly explained and the results of four test sites covering different climatic regions are evaluated. The different characteristics of the WAM using amplitude and coherence image are described and their respective pros and cons are discussed.
    EUSAR 2012; 01/2012
  • Chapter: TanDEM-X
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    ABSTRACT: TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) is a highly innovative Earth observation mission that opens a new era in remote sensing. TanDEM-X comprises two formation flying satellites, each equipped with a synthetic aperture radar (SAR) to map the Earth?s surface with high spatial resolution. Together, the two satellites form a unique single-pass SAR interferometer, offering the opportunity for flexible baseline selection. Primary objective of TanDEM-X is the acquisition of a global digital elevation model (DEM) with unprecedented accuracy and resolution (12 m horizontal and 2 m vertical resolution). Besides the primary mission goal, several secondary objectives based on along-track interferometry and new bistatic SAR techniques have been defined, representing a further important asset of the mission. TanDEM-X was successfully launched in June 2010 and started operational data acquisition in December 2010. This chapter outlines the TanDEM-X mission concept and its implementation, summarizes the main data processing and calibration steps, and provides an overview of the actual performance and mission status. Furthermore, results from several scientific experiments are presented, showing the great potential of future formation flying interferometric SAR missions to serve a wide spectrum of novel applications.
    Edited by Marco D'Errico, 01/2012: pages 387-435; Springer.
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    ABSTRACT: The main product of the TanDEM-X mission is a global interferometric digital elevation model (DEM) that is finally calibrated due to residual systematic offsets and tilts. For the final DEM product single acquisitions (so-called data takes) are calibrated and merged to tiles of a size of 1°x1°. Finally the globe will mostly be covered with two acquisitions. The quality of the calibration of the data takes and also the accuracy of the final DEM highly depends on the terrain and the vegetation. Therefore, three different test areas where we have to deal with good, medium and difficult terrain conditions will be presented here.
    9th European Conference on Synthetic Aperture Radar (EUSAR); 01/2012
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    ABSTRACT: 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.
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 01/2012; · 2.87 Impact Factor
  • IGARSS 2011; 07/2011
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    ABSTRACT: Additionally to the global DEM which is the main product of the TanDEM-X mission a global water body mask will be produced. The main goal of this water mask is to deliver an information layer for any subsequent DEM editing process. It is derived from the SAR amplitude and coherence. In this paper, the concept of the global water body detection is explained and a first evaluation of the single coverage water body detection is presented.
    IGARSS 2011; 01/2011
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    ABSTRACT: 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.
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS); 01/2011
  • Andreas Schmitt, Birgit Wessel, Achim Roth
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    ABSTRACT: 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 differentiation 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 crisis scenarios: flood, forest fire, and earthquake. For all scenarios including natural landscapes and urban environments 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 rescue teams after large-scale natural disasters. German Fernerkundung im Krisenkontext basiert auf einer schnellen und zuverlässigen Datenakquisition. Radarsysteme sind für diesen Zweck aufgrund ihrer i. A. wetter- und beleuchtungsunabhängigen Aufnahme besonders geeignet. In diesem Artikel wird eine Methode vorgestellt, aus zeitlich versetzten Aufnahmen des deutschen Radarsatelliten TerraSAR-X vollautomatisch Veränderungen abzuleiten. Die geokodierten Radaramplitudenbilder werden dazu logarithmisch skaliert und mithilfe der Curvelet-Transformation in den Curvelet-Koeffizientenraum überführt. Jeder Koeffizient entspricht hier der Stärke einer bestimmten linearen Struktur im Bild. Aus den Koeffizienten zweier Bilder kann nun ein Differenz-Koeffizientenbild berechnet und anschließend durch eine spezielle Gewichtungsfunktion verbessert werden. Während starke Strukturen unverändert übernommen werden, erfolgt für Strukturen mittlerer Stärke eine kontinuierliche Herabgewichtung bis zum kompletten Entfernen zu schwacher Strukturen. Auf diese Weise wird nicht nur die Anzahl der Koeffizienten, sondern auch das Rauschen im Bild deutlich verringert und der Bildinhalt auf die wichtigsten Strukturen beschränkt. Nach der Rücktransformation in den Bildraum und die ursprüngliche Skalierung kann die Änderung anteilig in Bezug auf die Ausgangsamplitude als Zu- und Abnahme dargestellt werden. Zur Demonstration des Potentials der Curvelet basierten Änderungserkennung werden drei Anwendungsfälle aus dem Krisenkontext vorgestellt: Überflutung, Waldbrand, Erdbeben. In allen drei Fällen lässt sich die von der Katastrophe betroffene Fläche eindeutig von Flächen ohne Änderung abgrenzen. Die Interpretation dieser Änderungen ist jedoch ohne Zusatzwissen nicht möglich. Eine Verschneidung der Ergebnisse der Änderungserkennung mit bestehenden Geoinformationen hingegen liefert eine verlässliche Datengrundlage für die Organisation von Rettungskräften nach Naturkatastrophen.
    Photogrammetrie - Fernerkundung - Geoinformation 11/2010; 2010(6):463-474. · 0.74 Impact Factor
  • Andreas Schmitt, Birgit Wessel, Achim Roth
    [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Photogrammetrie Fernerkundung Geoinformation. 11/2010; 2010(2010-11-6):467-478.
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    ABSTRACT: This article compares four different alternative image representations in the context of a structure-based change detection. The framework is taken from the already published Curvelet-based change detection approach. Only the transform step is modified by inserting three additional transforms: the Laplacian pyramid, the Wavelet and the Surfacelet transform. The results of the change detection are compared to the single pixel difference image in order to find the representation that best illustrates the underlying structures. The Curvelet transform again turns out to be very powerful in describing man-made objects and landscapes.
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International; 08/2010
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    Andreas Schmitt, Birgit Wessel, Achim Roth
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    ABSTRACT: In this article a new change detection approach for polarimetric SAR data is presented. The further development of an already published change detection approach based on Curvelet transform for single polarized SAR images is combined with partial polarimetric layers of a reduced Huynen decomposition. The data used has been ac-quired by TerraSAR-X in the High Resolution Spotlight mode with two polarization channels: HH and VV (dual-pol). The motivation for using polarimetric information is that it helps to interpret changes indicated by the change detection algorithm, so that plant growth or crop on agricultural land as well as water level variations in rivers or even small scale changes in industrial plants like harbors get clearly visible. The Curvelet-based change detection turns again out to be a powerful tool for SAR image handling – image enhancement and change detec-tion – whereas the polarimetric information about the underlying scattering mechanisms delivers astonishing re-sults.
    8th European Conference on Synthetic Aperture Radar; 07/2010
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    Thomas Hahmann, Birgit Wessel
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    ABSTRACT: This paper presents the application of two different active contour models for the segmentation of highresolution TerraSAR-X data. Both methods facilitate the detection of land-water-boundaries in semi-automated procedures and can be used to delineate flood extent and to map open water surfaces in general. For the extraction of smooth water bodies amplitude thresholding approaches are quite common and often applied. For rough water bodies however the application of amplitude thresholding methods is not successful. This paper demonstrates the potentials and limitations of active contour models for mapping both smooth and rough water bodies in high-resolution SAR data. Examples of both different segmentation methods are presented.
    Synthetic Aperture Radar (EUSAR), 2010 8th European Conference on; 07/2010
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    ABSTRACT: In the first half of 2010 the second satellite of the system TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X) will be launched from Baikonur Cosmodrome, the first one – TerraSAR-X - is already working since more than two years. The TanDEM-X satellite mission will provide a digital elevation model (DEM) from the complete Earth. The relative height accuracy will be approx. 2m, the resolution on ground will be better than 12m. Four DLR institutes are responsible for the SAR payload, mission control, receiving stations, interferometric SAR (InSAR) processing, product generation and archiving and web interface. The scientific user community can use this web interface to submit their proposals and order DEMs for there test sites. The German company Infoterra will support commercial users. Four DEM products are planed: Intermediate DEM (2.5 years after launch) with less accuracy, final DEM (4 years after launch) with the required quality, FDEM with a higher ground resolution and HDEM with a better height quality. The paper will also give an overview about this DLR processing chain. These system- and product accuracy requirements will be guaranteed by different calibration and validation approaches. One important reference source especially for the validation are kinematic GPS tracks with accuracies better than 0.5m. Due to the fact that either local reference station or any regional reference station network is worldwide available Precise Point Positioning was selected as post processing method. In 2009 several world-wide tracks were measured with this method in Argentina/Chile, Brazil, North America, Central Europe, Northwest Africa, East-West coast track in southern Africa, Russia and Central Asia. Tracks in India and Saudi-Arabia are ordered and will be carried out in spring 2010. More than 50 000km were measured from different teams. This paper will present the organisation, requirements and experiences during the tracks, examples of the products (height-profiles) and first results of these kinematic GPS tracks. In summer 2008 the Commission 5 published the announcement "Kinematic GNSS for Evaluation of TanDEM-X Digital Elevation Model" to support the German satellite mission “TanDEM-X”.
    The XXIV FIG International Congress 2010; 04/2010
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    ABSTRACT: 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 and if available on real TanDEM-X data. Also, the DEM calibration will be validated for the first time on a larger “real” test site by applying the TanDEM-X processing scenario.
    2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS); 01/2010
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    Andreas Schmitt, Birgit Wessel, Achim Roth
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    ABSTRACT: In this paper we present an alternative method for SAR image denoising, structure enhancement, and change detection based on the curvelet transform. Curvelets can be denoted as a two dimensional further development of the well-known wavelets. The original image is decomposed into linear ridge-like structures, that appear in different scales (longer or shorter structures), directions (orientation of the structure) and locations. The influence of these single components on the original image is weighted by the corresponding coefficients. By means of these coefficients one has direct access to the linear structures present in the image. To suppress noise in a given SAR image weak structures indicated by low coefficients can be suppressed by setting the corresponding coefficients to zero. To enhance structures only coefficients in the scale of interest are preserved and all others are set to zero. Two same-sized images assumed even a change detection can be done in the curvelet coefficient domain. The curvelet coefficients of both images are differentiated and manipulated in order to enhance strong and to suppress small scale (pixel-wise) changes. After the inverse curvelet transform the resulting image contains only those structures, that have been chosen via the coefficient manipulation. Our approach is applied to TerraSAR-X High Resolution Spotlight images of the city of Munich. The curvelet transform turns out to be a powerful tool for image enhancement in fine-structured areas, whereas it fails in originally homogeneous areas like grassland. In the change detection context this method is very sensitive towards changes in structures instead of single pixel or large area changes. Therefore, for purely urban structures or construction sites this method provides excellent and robust results. While this approach runs without any interaction of an operator, the interpretation of the detected changes requires still much knowledge about the underlying objects.
    City Models, Roads and Traffic (CMRT); 09/2009
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    Astrid Gruber, Birgit Wessel, Martin Huber
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    ABSTRACT: This paper gives an overview of the DEM adjustment within the TanDEM-X mission. The DEM adjustment estimates residual, systematic height offsets and deformations of each single interferometric DEM acquisition. The challenge of calibrating the TanDEM-X DEMs lies in the magnitude of the systematic errors: these errors are in the same order like the random error of about 2 m. For the estimation of the corrections a least-squares adjustment of adjacent, overlapping interferometric DEMs over a certain earth region is described in this paper. Adjustment results on simulated DEM data are shown to validate the approach. The tests are carried out for different dense ground control point configurations. Further the improvements by a combined adjustment of the two coverages are demonstrated.
    2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS); 08/2009

Publication Stats

161 Citations
9.39 Total Impact Points

Institutions

  • 2008–2012
    • German Aerospace Center (DLR)
      • German Remote Sensing Data Center (DFD)
      Köln, North Rhine-Westphalia, Germany
    • Center for Remote Sensing and Ocean Science
      Batavia, Jakarta Raya, Indonesia
  • 2001–2006
    • Technische Universität München
      • Chair of Photogrammetry and Remote Sensing
      München, Bavaria, Germany