TanDEM-X calibrated Raw DEM generation

Rossi, Cristian; González, Fernando Rodríguez; Fritz, Thomas; Yague-Martinez, Nestor; Eineder, Michael

doi:10.1016/j.isprsjprs.2012.05.014

Cited by 152 publications

(115 citation statements)

References 16 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: 87%

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: 87%

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

et al. 2017

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“…Data were processed into Raw DEM products by the Integrated TanDEM-X Processor (ITP) [39]. This procedure includes all steps necessary to interferometrically process the data into geocoded height maps including co-registration, phase unwrapping and geocoding.…”

Section: Insar-derived Digital Elevation Modelsmentioning

confidence: 99%

A Glacier Surge of Bivachny Glacier, Pamir Mountains, Observed by a Time Series of High-Resolution Digital Elevation Models and Glacier Velocities

et al. 2017

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Surge-type glaciers are characterised by relatively short phases of enhanced ice transport and mass redistribution after a comparatively long quiescent phase when the glacier is virtually inactive. This unstable behaviour makes it difficult to assess the influence of climate change on those glaciers. We describe the evolution of the most recent surge of Bivachny Glacier in the Pamir Mountains, Tajikistan between 2011 and 2015 with respect to changes in its topography and dynamics. For the relevant time span, nine digital elevation models were derived from TanDEM-X data; optical satellite data (Landsat 5, 7 and 8, EO-1) as well as synthetic aperture radar data (TerraSAR-X and TanDEM-X) were used to analyse ice flow velocities. The comparison of the topography at the beginning of the surge with the one observed by the Shuttle Radar Topography Mission in 2000 revealed a thickening in the upper part of the ablation area of the glacier and a thinning further down the glacier as is typically observed during the quiescent phase. During the active phase, a surge bulge measuring up to around 80 m developed and travelled downstream for a distance of 13 km with a mean velocity of 4400 m year −1 . Ice flow velocities increased from below 90 m year −1 duringthe quiescent phase in 2000 to up to 3400 m year −1 in spring 2014. After reaching the confluence with Fedchenko Glacier, the surge slowed down until it completely terminated in 2015. The observed seasonality of the glacier velocities with a regular speed-up during the onset of the melt period suggests a hydrological control of the surge related to the effectiveness of the subglacial drainage system.

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“…Then, this DEM is employed as an external DEM in phase unwrapping process. The phase offset is calculated from the mean of the most probable values in the phase difference histogram (histogram of radargrammetric and unwrapped phase difference), whereas layover and shadow areas are disregarded (Rossi et al, 2012). In consequence, for areas affected by layover or shadowing, such as subset C (high buildings), the vertical offset is higher than in the other test subsets because they are discarded for phase offset estimation and the vertical offset estimate is not valid for these areas.…”

Section: Study Area and Demsmentioning

confidence: 99%

Uncertainty Assessment and Weight Map Generation for Efficient Fusion of Tandem-X and Cartosat-1 Dems

Bagheri

Schmitt

Zhu

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Recently, with InSAR data provided by the German TanDEM-X mission, a new global, high-resolution Digital Elevation Model (DEM) has been produced by the German Aerospace Center (DLR) with unprecedented height accuracy. However, due to SAR-inherent sensor specifics, its quality decreases over urban areas, making additional improvement necessary. On the other hand, DEMs derived from optical remote sensing imagery, such as Cartosat-1 data, have an apparently greater resolution in urban areas, making their fusion with TanDEM-X elevation data a promising perspective. The objective of this paper is two-fold: First, the height accuracies of TanDEM-X and Cartosat-1 elevation data over different land types are empirically evaluated in order to analyze the potential of TanDEM-XCartosat-1 DEM data fusion. After the quality assessment, urban DEM fusion using weighted averaging is investigated. In this experiment, both weight maps derived from the height error maps delivered with the DEM data, as well as more sophisticated weight maps predicted by a procedure based on artificial neural networks (ANNs) are compared. The ANN framework employs several features that can describe the height residual performance to predict the weights used in the subsequent fusion step. The results demonstrate that especially the ANN-based framework is able to improve the quality of the final DEM through data fusion.

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TanDEM-X calibrated Raw DEM generation

Cited by 152 publications

References 16 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

A Glacier Surge of Bivachny Glacier, Pamir Mountains, Observed by a Time Series of High-Resolution Digital Elevation Models and Glacier Velocities

Uncertainty Assessment and Weight Map Generation for Efficient Fusion of Tandem-X and Cartosat-1 Dems

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