Development of the TanDEM-X Calibration Concept: Analysis of Systematic Errors

González, Jaime Hueso; Bachmann, Markus; Krieger, Gerhard; Fiedler, Hauke

doi:10.1109/tgrs.2009.2034980

Cited by 75 publications

(66 citation statements)

References 12 publications

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“…The residual phase trend is caused by small errors in the satellite positions, which result in baseline errors. Similar trends have been reported by other authors [6,15,16,21,49]. The error is easily observed in overlapping areas between adjacent swaths and can be corrected, to first order, by fitting an error model to the data.…”

Section: Scenes With Phase Trendssupporting

confidence: 88%

Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data

et al. 2017

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This paper report experiences from the processing and mosaicking of 518 TanDEM-X image pairs covering the entirety of Sweden, with two single map products of above-ground biomass (AGB) and forest stem volume (VOL), both with 10 m resolution. The main objective was to explore the possibilities and overcome the challenges related to forest mapping extending a large number of adjacent satellite scenes. Hence, numerous examples are presented to illustrate challenges and possible solutions. To derive the forest maps, the observables backscatter, interferometric phase height and interferometric coherence, obtained from TanDEM-X, were evaluated using empirical robust linear regression models with reference data extracted from 2288 national forest inventory plots with a 10 m radius. The interferometric phase height was the single most important observable, to predict AGB and VOL. The mosaics were evaluated on different datasets with field-inventoried stands across Sweden. The root mean square error (RMSE) was about 21%-25% (27-30 tons/ha and 52-65 m 3 /ha) at the stand level. It was noted that the most influencing factors on the observables in this study were local temperature and geolocation errors that were challenging to robustly compensate against. Because of this variability at the scene-level, determinations of AGB and VOL for single stands are recommended to be used with care, as an equivalent accuracy is difficult to achieve for all different scenes, with varying acquisition conditions. Still, for the evaluated stands, the mosaics were of sufficient accuracy to be used for forest management at the stand level.

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Section: Scenes With Phase Trendssupporting

confidence: 88%

Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data

et al. 2017

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“…The expected root-mean-square error (RMSE) for the ASTER GDEM depends on topography and number of observations available, ranging from 3 to 50 m (Reuter et al, 2009;Hirt et al, 2010;Hengl and Reuter, 2011). The TanDEM-X DEM is expected to provide 10 m absolute and 2-4 m relative vertical accuracy (Gonzalez et al, 2010). ICESat altimeter data are accurate to ∼ 0.3 m in the vertical (Magruder et al, 2007).…”

Section: Digital Elevation Model (Dem)mentioning

confidence: 99%

Surface velocity and mass balance of Livingston Island ice cap, Antarctica

Osmanoǧlu

Navarro²,

Hock

et al. 2014

The Cryosphere

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Abstract. The mass budget of the ice caps surrounding the Antarctica Peninsula and, in particular, the partitioning of its main components are poorly known. Here we approximate frontal ablation (i.e. the sum of mass losses by calving and submarine melt) and surface mass balance of the ice cap of Livingston Island, the second largest island in the South Shetland Islands archipelago, and analyse variations in surface velocity for the period 2007-2011. Velocities are obtained from feature tracking using 25 PALSAR-1 images, and used in conjunction with estimates of glacier ice thicknesses inferred from principles of glacier dynamics and ground-penetrating radar observations to estimate frontal ablation rates by a flux-gate approach. Glacier-wide surface mass-balance rates are approximated from in situ observations on two glaciers of the ice cap. Within the limitations of the large uncertainties mostly due to unknown ice thicknesses at the flux gates, we find that frontal ablation (−509± 263 Mt yr −1 , equivalent to −0.73 ± 0.38 m w.e. yr −1 over the ice cap area of 697 km 2 ) and surface ablation (−0.73 ± 0.10 m w.e. yr −1 ) contribute similar shares to total ablation (−1.46 ± 0.39 m w.e. yr −1 ). Total mass change (δM = −0.67 ± 0.40 m w.e. yr −1 ) is negative despite a slightly positive surface mass balance (0.06± 0.14 m w.e. yr −1 ). We find large interannual and, for some basins, pronounced seasonal variations in surface velocities at the flux gates, with higher velocities in summer than in winter. Associated variations in frontal ablation (of ∼ 237 Mt yr −1 ; −0.34 m w.e. yr −1 ) highlight the importance of taking into account the seasonality in ice velocities when computing frontal ablation with a flux-gate approach.

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“…The third mode is adopted in this study, as it is commonly used in monitoring land masses, whereas the other two are not designed for DEM generation. It is reported that the absolute vertical height specification accuracy of TSX/TDX DEM is 10 m (90% linear error), and the relative accuracy is ~2 m for areas with predominant terrain slopes that are smaller than 20° [27,37,40,41].…”

Section: Terrasar-x/tandem-xmentioning

confidence: 99%

“…Absolute height accuracy is a common criterion to assess InSAR DEMs based on the accurate traditional outcomes, such as GPS and LiDAR [40,41]. However, in some areas, ground control points is lacking or difficult to collect.…”

Section: Relative Height Accuracymentioning

confidence: 99%

“…A considerable number of studies have been conducted based on TSX/TDX data. For example, 3D topographic reconstruction, fusion of ascending and descending images, phase unwrapping and filtering [28][29][30][31][32], large-scale deformation monitoring e.g., volcano and glacier [33][34][35], relative and absolute accuracy assessment of TSX/TDX DEM [36][37][38][39][40][41], terrain classification and forest height and biomass inversion [42,43]. The accumulated TSX/TDX image pairs acquired over the years can be used to generate a set of DEMs over the same area, which is particularly helpful for investigating the temporal evolution of natural hazards, e.g., landslides.…”

Section: Introductionmentioning

confidence: 99%

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Recent Landslide Movement in Tsaoling, Taiwan Tracked by TerraSAR-X/TanDEM-X DEM Time Series

Liu

Zhang

et al. 2017

Remote Sensing

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Abstract:The Tsaoling Landslide in Taiwan has captured attentions of researchers worldwide due to its frequent catastrophic failure and distinctive features. Thanks to the launch of TerraSAR-X/TanDEM-X (TSX/TDX) constellation, retrieval of global DEM with high spatial resolution and accuracy becomes possible, which is extremely useful for the study of natural hazards (e.g., landslides) globally. We attempt here for the first time to track recent landslide movements in Tsaoling Taiwan by analyzing DEM time series reconstructed from TSX/TDX image pairs. Quality improvement of InSAR derived DEM through an iterated differential operation is addressed during the data processing.

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Development of the TanDEM-X Calibration Concept: Analysis of Systematic Errors

Cited by 75 publications

References 12 publications

Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data

Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data

Surface velocity and mass balance of Livingston Island ice cap, Antarctica

Recent Landslide Movement in Tsaoling, Taiwan Tracked by TerraSAR-X/TanDEM-X DEM Time Series

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