Lachaise, Marie

Schweißhelm, Barbara

The TanDEM-X mission has acquired multiple global coverages of data over the last years in order to create digital elevation models (DEMs). The data between 2017 and 2020 is processed to Change RawDEMs (CRaw DEMs). These scenes are successfully pre-calibrated individually during the processing. However, in order to determine and quantify terrain changes between the new data and the former global TanDEM-X DEM, the calibration can be improved even further. In the case of large-scale terrain changes like glaciers or forestation areas CRaw DEMs might be calibrated on the change instead of the smaller stable regions. A comparison of to the calibration of neighboring scenes gives information on which scene has to be corrected. This paper summarizes the pre-calibration during the processing of the CRaw DEMs and analyzes the results of the calibration and corresponding change detection. Furthermore, a method for a post-calibration of the CRaw DEMs is presented. This method will be used to create TanDEM-X DEM Change Maps in the future

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CALIBRATION OF THE TANDEM-X CRAW DEMS FOR THE TANDEM-X DEM CHANGEMAPS GENERATIONBarbara Schweisshelm, Marie LachaiseRemote Sensing Technology Institute, German Aerospace Center (DLR)Münchner Str. 20, 82234 Oberpfaffenhofen, Germanybarbara.schweisshelm@dlr.deABSTRACTThe TanDEM-X mission has acquired multiple global cover-ages of data over the last years in order to create digital el-evation models (DEMs). The data between 2017 and 2020is processed to Change RawDEMs (CRaw DEMs). Thesescenes are successfully pre-calibrated individually during theprocessing. However, in order to determine and quantify ter-rain changes between the new data and the former globalTanDEM-X DEM, the calibration can be improved even fur-ther. In the case of large-scale terrain changes like glaciersor forestation areas CRaw DEMs might be calibrated on thechange instead of the smaller stable regions. A comparisonof to the calibration of neighboring scenes gives informa-tion on which scene has to be corrected. This paper summa-rizes the pre-calibration during the processing of the CRawDEMs and analyzes the results of the calibration and corre-sponding change detection. Furthermore, a method for a post-calibration of the CRaw DEMs is presented. This method willbe used to create TanDEM-X DEM Change Maps in the fu-ture.Index Terms— TanDEM-X mission, TanDEM-X DEM2020, DEM calibration, terrain changes1. INTRODUCTIONSince 2010 the TanDEM-X mission flies the similar satel-lites TerraSAR-X and TanDEM-X as a bistatic interferometerto create digital elevation models (DEMs). The data set forthe first global DEM was acquired between the years 2010 -2015 to generate the global TanDEM-X DEM from the datain 2016. After that it was decided to continue the data acqui-sition in order to gain a second global DEM coverage [1]. TheTanDEM-X DEM 2020 (formerly called TanDEM-X ChangeDEM) [2] will be the second global Digital Elevation Model(DEM) of the TanDEM-X Mission. This second data set wasmainly acquired between 2017 and 2020. Due to the limitedacquisition and downlink resources, there will only be onecoverage of data for many areas of the world in this data set.The temporal independence between the two data sets yieldthe possibility of accurate terrain change detection.For the TanDEM-X DEM 2020, the individual data scenes areprocessed to so-called Change Raw DEMs (CRaw DEMs) bythe Integrated TanDEM-X Processor (ITP) [3]. The CRawDEMs are mosaicked to the global TanDEM-X DEM 2020 bythe Mosaicking and Calibration Processor (MCP) [4]. How-ever, this paper focuses on the intermediate product of theCRaw DEMs which are pre-calibrated DEM-scenes with anextent of approximately 30 km x 50 km. All CRaw DEMsown a precise time tag and can therefore provide an even morevaluable change data set. For terrain change detection a pre-cise calibration is essential. Therefore the calibration of theCRaw DEMs and their post-processing calibration which im-proves the quality of terrain change detection are discussed inthe following.2. INTERFEROMETRIC PROCESSING OF THECRAW DEMSThe interferometric processing of the CRaw DEMs is doneby the ITP. The processing had to be adjusted in compari-son to the processing of the first global TanDEM-X DEM be-cause for considerable areas of the Earth there is only onenew coverage of data. For that reason the dual-baseline al-gorithm [5] is not feasible anymore and the so-called delta-phase algorithm was developed [3]. This algorithm uses areference DEM. For the TanDEM-X DEM 2020 the referenceDEM is an edited version of the TanDEM-X global DEM.There are different edited versions of the TanDEM-X globalDEM used for the processing of CRaw DEMs. All the ex-amples within this paper were processed with a 30m-postingTanDEM-X DEM edited by DLR [6]. The reference DEM isused to simulate a phase which is subtracted from the interfer-ometric phase instead of a flat Earth equivalent. This reducesthe fringe frequency and flattens the interferometric phase. Asa consequence the time and error rate of the phase unwrappingare reduced immensely. Because the reference DEM is addedagain to the unwrapped data, the final DEM values are mostlyindependent of the height values of the reference DEM.3. CALIBRATION OF THE CRAW DEMSThe usage of a reference DEM does not only improve thephase unwrapping but is also used to calibrate the processedCRaw DEM scenes individually. This means that the CRawDEMs, which are processed with the edited version of theglobal TanDEM-X DEM, are located exactly on top of theglobal TanDEM-X DEM. If a CRaw DEM scene includes ter-rain changes within a small area, the procedure works well.However, if a CRaw DEM includes large-area terrain changeslike melted glaciers or large forestation areas, in some casesthe CRaw DEM is calibrated wrongly on the changed area,because it represents the main part of the scene.3.1. Calibration ProcedureThe calibration of each CRaw DEM takes place during theindividual processing of the corresponding scene. The proce-dure, roughly explained in [7], is illustrated and analyzed inmore detail in the following.The delta-phase, the difference of the interferometric phaseand the simulated phase from the reference DEM, is the start-ing point of the calibration. By creating a histogram, the ap-proximate offset is estimated. It is assumed that most part ofthe scene has not changed and therefore the highest peak be-longs to the overall offset. When there is a large-scale uniformterrain change however, it can happen that the calibration doesnot work correctly. All pixels within a threshold around thisfirst offset are then considered for a fit. The threshold is cho-sen in order to exclude areas where the terrain height changedw.r.t. the main part of the scene. This step fits a plane to thedelta phase values with two parameters. One is the final off-set between the scene and the reference DEM. The second isa trend in azimuth direction. This trend is used to compensatefor possible baseline uncertainties. It is restricted to valuesbetween -2 m and 2 m over the whole azimuthal dimensionof the scene. This restriction is used to not fit largescale ter-rain changes with trends and stay within reasonable bounds.The good quality of the baseline calibration can only lead tominor trends. After the fit each scene is separately correctedwith its overall offset and azimuthal trend, which is illustratedin Fig. 1.3.2. CRaw DEM Calibration ResultsThis subsection portrays the results of the scene wise calibra-tion. At first, the statistical distribution of the azimuth trend isgiven in Fig. 2. The histogram is calculated for a subsampleof 27378 CRaw DEMs processed in September of 2021 forthe TanDEM-X DEM 2020. It demonstrates that the cut at±2 m is valid, because only a minority of values are close tothis cut (logarithmic scale). Furthermore, it shows that mostscenes encounter no or only a very small trend in azimuthwhich confirms the good quality of the baselines.Fig. 1. Illustration of the scene wise calibration process dur-ing the CRaw DEM processing. The black lines and arrowsillustrate the two fit parameters (offset and azimuth trend) foreach of the two CRaw DEM.Fig. 2. Distribution of the azimuth trend of CRaw DEMscenes. This plot is created with a subsample of 27378 scenes,processed in September of 2021.A statistical distribution of the second parameter of the fit,the offset, is omitted because the random, ambiguous distri-bution of a phase offset does not give additional informationabout the calibration performance.Additional to the statistical distribution of the calibration,a specific example of two overlapping scenes gives an impres-sion of the accuracy of the calibration during the ITP process-ing. The example region is a mining area within Brazil. TwoCRaw DEMs from the same acquisition are chosen. The ITPis configured in a way that neighboring scenes of the samedata take overlap by one second. The corresponding CRawDEMs are shown in Fig. 4 (a) and Fig. 5 (a). In order to createFig. 3 (a) the difference of the two CRaw DEMs in the over-lap region is calculated. The corresponding histogram for thedifferences in height is given in Fig. 3 (b) within a range of±2 m. The overall offset between the two scenes which is es-timated from the histogram is below 10 cm. Even though thisis only one specific example, it is exemplary for most cases(a) Difference between the DEM height values in theoverlapping area of two neighboring scenes.(b) Histogram corresponding to the difference between the .DEM height values in the overlapping area.Fig. 3. Example for the calibration of two overlapping scenesover a mining area in Brazil.of C-Raw DEM scenes which do include no or small-scaleterrain changes like mining areas.4. TERRAIN CHANGES AND CRAW DEMSThe possibility for the detection of terrain changes within thedata of the TanDEM-X DEM 2020 is presented in [7]. Withinthis section the terrain changes between the CRaw DEMsand the reference DEM for the previously discussed Brazil-ian mining area are presented.4.1. Change Indication Mask and Delta HeightA Change Indication Mask (CHM) is produced during theprocessing of each single CRaw DEM scene. It distinguishesbetween significant or non-significant and reliable or non-reliable changes. A significant terrain change is character-ized by a regional height difference which exceeds a certainthreshold. A reliable change refers to a region in the referenceDEM with original TanDEM-X data. The Delta Height imagegives the corrected unwrapped delta phase image convertedto meters.The CHM (b) and Delta Height (c) are shown in Fig. 4 andFig. 5 for parts of the CRaw DEMs over Brazil. The areais marked with a yellow box in the corresponding CRawDEM images. The CHMs show where reliable and signifi-cant changes (light green) appear. They agree nicely with thechanged areas in the Delta Height image and the position ofthe mines.(a) CRaw DEM(b) CHM (c) Delta HeightFig. 4. CRaw DEM products of a scene over a mining area inBrazil. The yellow box in the CRaw DEM shows which partis shown in the CHM and Delta Height.4.2. Potential Error SourcesThe CHMs and Delta Heights of the CRaw DEMs show thepotential of change detection with the new data. However,these potential terrain changes have to be taken with cautionbecause there are still potential error sources which have tobe accounted for. The following list gives the most promi-nent sources for error within the terrain change detection fromCRaw DEMs• Phase unwrapping (PU) errors• Calibration errors or inaccuracy• Shadow or layover effects (different acquisition geom-etry)(a) CRaw DEM(b) CHM (c) Delta HeightFig. 5. CRaw DEM products of a scene over a mining area inBrazil. The yellow box in the CRaw DEM shows which partis shown in the CHM and Delta Height.Although all these effects are important, within the scope ofthis paper only the calibration inaccuracies will be discussed.4.3. Post processing calibrationThe calibration during the processing of the CRaw DEMs issufficient in up to 99 % of the scenes. The non-sufficientlycalibrated scene mostly include large-scale uniform terrainchanges and are therefor calibrated with this changed area onthe reference DEM. However, in order to detect and quantifyreliable terrain changes, badly calibrated CRaw DEMs haveto be corrected. This is why for the DEM Change Maps prod-uct [8] the CRaw DEMs are re-calibrated before they are jointto DEM Change Map tiles. This re-calibration is going to beperformed for every data take individually. Calculating theexact average difference between two scenes within the over-lapping area is much more time and resource consuming thancomparing the fitted planes (cp. section 3.1) of the CRawDEMs. However, the second option provides sufficient infor-mation for an evaluation of the calibration. Therefore, the gapbetween the overlap of two planes is calculated in the middlethe overlapping area with the help of the fit results. If the dif-ference exceeds a threshold (depending on the average heighterror) the scene is marked and a re-calibration is going to beperformed.5. CONCLUSIONThis paper aims to explain the calibration and terrain changedetection process during the processing of the CRaw DEMsfor the TanDEM-X DEM 2020. It also explains when thescene wise calibration encounters difficulties. Furthermore,it gives an outlook on how the calibration will be improvedin the future in order to allow a more accurate terrain changedetection within the context on the DEM Change Maps.6. REFERENCES[1] S. Buckreuss, “TerraSAR-X and TanDEM-X MissionStatus,” European Conference on Synthetic ApperatureRadar (EUSAR), pp. 1–4, 2018.[2] Marie Lachaise, Markus Bachmann, Thomas Fritz, Mar-tin Huber, Barbara Schweisshelm, and Birgit Wessel,“The tandem-x change dem: the new temporal dem ofthe tandem-x mission,” in EUSAR 2021; 13th EuropeanConference on Synthetic Aperture Radar, 2021, pp. 1–6.[3] M. Lachaise and T. Fritz, “Update of the interferometricprocessing algorithms for the TanDEM-X high resolutionDEMs,” in EUSAR 2016: 11th European Conference onSynthetic Aperture Radar. VDE, 2016, pp. 1–4.[4] Birgit Wessel, Ursula Marschalk, Astrid Gruber, Mar-tin Huber, Thomas Hahmann, Achim Roth, and MartinHabermeyer, “Design of the dem mosaicking and cali-bration processor for tandem-x,” in 7th European Con-ference on Synthetic Aperture Radar, 2008, pp. 1–4.[5] M. Lachaise, T. Fritz, and R. Bamler, “The dual-baseline phase unwrapping correction framework for theTanDEM-X mission part 1: Theoretical description andalgorithms,” 2017, vol. 56, pp. 780–798, IEEE.[6] C. González, M. Bachmann, J. Bueso-Bello, P. Rizzoli,and M. Zink, “A fully automatic algorithm for editing thetandem-x global dem,” Remote Sensing, vol. 12, no. 23,2020.[7] Barbara Schweisshelm, Marie Lachaise, and ThomasFritz, “Change detection within the processing of thetandem-x change dem,” in 2021 IEEE International Geo-science and Remote Sensing Symposium IGARSS. IEEE,2021, pp. 2130–2133.[8] Marie Lachaise, Carolina González, Paola Rizzo-liand Barbara Schweißhelm, and Manfred Zink, “’thenew tandem-x dem change maps product’,” in 2022 IEEEInternational Geoscience and Remote Sensing Sympo-sium IGARSS. IEEE, 2022.

Calibration of the TANDEM-X CRaw DEMs for the TANDEM-X DEM Change Maps Generation

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