Curvelet Approach for SAR Image Denoising, Structure Enhancement, and Change Detection

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

TanDEM-X Ground Segment – DEM Products Specification Document

The purpose of this document is to describe the TanDEM-X DEM products, their specifications and formats.The chapter 4 introduces the main DEM product, and its variants. The target accuracies are presented (Section 4.1.) and the DEM generation process is shortly summarized in Section 4.2.. The DEM product specifications are given in Section 4.3. Therein, the accuracy and grid definitions (Section 4.3.1) all information layers are described (Section 4.3.2). Information about the structure of the DEM product is provided in Section 4.3.3. Section 4.4. gives a short summary about the characteristics of the Intermediate DEM Product and future FDEM and HDEM products. In the Appendices an introduction to the XML schema, product parameters and change log information are described. Please note that the current XSDs are appended to this document

The TerraSAR-X Orthorectification Service and its Benefit for Land Use Applications

The German Aerospace Center (DLR) currently develops the TerraSAR-X Payload Ground Segment. On request level 1b products will be distributed to the user. Two of the four basic products available are generated by the geocoding system. This system supports ellipsoid and terrain correction in order to provide orthorectified images. A new product called Enhanced Ellipsoid Corrected (EEC) will be offered that considers Digital Elevation Models (DEMs) of a moderately coarser resolution than the resolution of the TerraSAR-X modes. SRTM/X-band DEMs with approximately 25 m resolution will be the backbone for this operational and fully automated service. For high precision terrain correction first results of an experimental processor are presented using a high resolution DEM, tie-pointing and image adjustment

A new high-resolution elevation model of Greenland derived from TanDEM-X

In this paper we present for the first time the new digital elevation model (DEM) for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement) mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR) DEM scenes. X- Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite) elevations as ground control points (GCPs) are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic

Performance evaluation of Sentinel-1 derived DEMs using Copernicus DEM and ICESat-2

Digital elevation models (DEMs) hold a key role as the main input data for a large variety of applications as they provide an accurate representation of the Earth’s surface and its corresponding topographic parameters. Scientific applications require current, reliable and precise elevation information to be implemented in research to generate correct and valuable results. The performance and accuracy of DEMs must therefore be subject to quality assessment. Synthetic Aperture Radar (SAR) principles and methodology allow the generation of DEMs independent from day light and cloud coverage which act as a massively limiting interference factor in optical imagery. In 2014, a C-band radar mission Sentinel-1 launched within the Copernicus Programme of the European Space Agency (ESA), providing open access to radar data of regular global coverage (Braun 2021). The capabilities of DEM derivation from Sentinel-1 imagery are limited by parameters like slope and vegetation coverage as well as by the mission design itself as the large temporal baseline of two or more Sentinel-1 acquisitions hinders the stability of the interferometric phase and degrades the coherence. One crucial step in the analysis of SAR data and therefore optimizing its potential for DEM generation is the preprocessing of suitable interferometric data pairs, a complex workflow which includes coregistration, interferogram formation, phase unwrapping and terrain correction (Braun 2021). Within the scope of the TanDEM-X mission by the German Aerospace Center (DLR), consisting of two satellites (Terra-SAR-X and Tandem-X), a global DEM was generated from bistatic X-Band interferometric SAR products acquired between December 2010 and January 2015 (Rizzoli 2017). The TanDEM-X mission is the original source of the radar data from which the Copernicus DEM (COP-DEM) by ESA was derived. The COP-DEM is available in varying resolutions with the 30m resolution COP-DEM being openly accessible. The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission by National Aeronautics and Space Administration (NASA) provides openly accessible data since October 2018. ICESat-2 data is a continuous, equally distributed, high resolution reference dataset and allows to independently evaluate the performance of SAR-derived DEMs. An Advanced Topographic Laser Altimeter System (ATLAS) on board of ICESat-2 fires shots of photons in 532nm wavelength separated into six beams arranged in three pairs. Each pair consists of a strong and a weak beam with an energy ratio of 4:1 (Neuenschwander und Pitts 2019). Terrain and canopy heights retrievals are stored in the ATL08 data product of ICESat-2 and computed for fixed 12x100m land segments in which a valid height value is given if a threshold of 50 signal photons is met in order to reliably represent the land surface within the segment. ICEsat-2 provides a large variety of parameters and flags to filter the data adapted to the needs of the research purpose. In this paper, we will generate several DEMs derived from Sentinel-1 data and perform a quality and accuracy evaluation. As reference data, we will use highly accurate ICESat-2 data points and two reference DEMs, TanDEM-X in 10m resolution and Copernicus DEM in 30m resolution. The main focus of this study is the correct processing and application of various parameter filter techniques of ICESat-2 data to provide accurate height reference data for the accuracy assessment of SAR-derived DEMs and the evaluation on DEM quality in consideration of different land cover types and topographic conditions regarding study sites from different continents

Assessment of TanDEM-X DEM 2020 Data in Temperate and Boreal Forests and Their Application to Canopy Height Change

Space-borne digital elevation models (DEM) are considered as important proxy for canopy surface height and its changes in forests. Interferometric TanDEM-X DEMs were assessed regarding their accuracy in forests of Germany and Estonia. The interferometric synthetic aperture radar (InSAR) data for the new global TanDEM-X DEM 2020 coverage were acquired between 2017 and 2020. Each data acquisition was processed using the delta-phase approach for phase unwrapping and comprise an absolute height calibration. The results of the individual InSAR heights confirmed a substantial bias in forests. This was indicated by a mean error (ME) between -5.74 and -6.14 m associated with a root-mean-squared-error (RMSE) between 6.99 m and 7.40 m using airborne light detection and ranging (LiDAR) data as a reference. The bias was attributed to signal penetration, which was attempted to be compensated. The ME and RMSE improved substantially after the compensation to the range of -0.54 to 0.84 m and 3.55 m to 4.52 m. Higher errors of the penetration depth compensated DEMs compared to the original DEMs were found in non-forested areas. This suggests to use the penetration compensation only in forests. The potential of the DEMs for estimating height changes was further assessed in a case study in Estonia. The canopy height change analysis in Estonia indicated an overall accuracy in terms of RMSE of 4.17 m and ME of -0.93 m on pixel level comparing TanDEM-X and LiDAR height changes. The accuracy improved substantially at forest stand level to an RMSE of 2.84 m and an ME of -1.48 m. Selective penetration compensation further improved the height change estimates to an RMSE of 2.14 m and an ME of -0.83 m. Height loss induced by clearcutting was estimated with an ME of -0.85 m and an RMSE of 3.3 m. Substantial regrowth resulted in an ME of -0.46 m and an RMSE of 1.9 m. These results are relevant for exploiting multiple global acquisitions of TanDEM-X, in particular for estimating canopy height and its changes in European forests

TanDEM-X DEM 2020: What is new?

In the last years, the TanDEM-X mission systematically acquired data to create another global DEM, the so-called 'TanDEM-X DEM 2020', mainly between September 2017 and mid-2020. This contribution describes the status of the generation of this second global TanDEM-X DEM with special focus on procedural and algorithmic modifications compared to the first global TanDEM-X DEM

Shaping the Global High-Resolution TanDEM-X Digital Elevation Model

The global digital elevation model (DEM) produced by the TanDEM-X (TerraSAR-X add-on for digital elevation measurements) mission is an interferometric elevation model with unprecedented quality, accuracy, and coverage. It represents an unedited surface model as artifacts inherent to the interferometric synthetic aperture radar acquisition and processing technique are still present. The most prominent artifacts in the DEM are water bodies appearing with a rough surface due to low coherence. Additionally, outliers, voids, and larger data gaps may be present in this dataset. Therefore,DEM editing is crucial for many applicationsincluding hydrology or orthorectification of remote sensing data. Depending on the field of application, different techniques of quality enhancement are required. This article provides a comprehensive description of a semi-automatic framework specially developed for generating an edited version of the TanDEM-X dataset by shaping the high-resolution 12 m DEM with focus on water areas, outlier handling, and void filling. The default configuration parameters of the workflow can thereby be adapted interactively for challenging areas where appropriate. A quality assessment of the resulting edited DEM was done by statistical measures, visual methods, as well as by an artifact evaluation

Urban correction for the hydrological conditioning of the TanDEM-X DEM for the HydroSHEDS v2 database

The HydroSHEDS database provides global hydrographic data for hydrological applications. The second, refined version of the database is improved by using the highresolution TanDEM-X digital elevation model (DEM). In order to derive hydrologic data from the terrain, during the socalled pre-conditioning, the DEM is edited and ancillary layers are calculated. Prior steps of the editing include, among others like void and outlier correction and the derivation of a coastline and water body mask, an urban correction. When river networks are derived from a DEM, visible artificial structures can divert the streams as they intercept the natural course of the riverbed. Therefore, during the last step of the pre-conditioning, the urban correction aims to reduce such diversions caused by built-up structures