Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data

Wessel, Birgit; Huber, Martin; Wohlfart, Christian; Marschalk, Ursula; Kosmann, Detlev; Roth, Achim

doi:10.1016/j.isprsjprs.2018.02.017

Cited by 329 publications

(262 citation statements)

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“…This is the result of topographic complexity below the resolution of the sensor, radar geometry considerations (layover, foreshortening, and shadowing), and interferometric phase unwrapping errors, all most pronounced in steep mountains. Such terrain biases are demonstrated in the SRTM-C with elevation (Berthier et al, 2006;Paul, 2008), slope and aspect (Gorokhovich and Voustian-15 iouk, 2006;Van Niel et al, 2008;Peduzzi et al, 2010;Shortridge and Messina, 2011), and resolution (manifested in curvature) (Gardelle et al, 2012), and in the TanDEM-X with only slope (Purinton and Bookhagen, 2017;Wessel et al, 2018). Terrain slope-also related to relief (Fig.…”

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confidence: 89%

“…On the other hand, the newer TanDEM-X apparently has far fewer biases related to satellite geometry, and most error is restricted to terrain characteristics like slope and vegetation, though results are still nascent (e.g., Baade and Schmullius, 2016;Purinton and Bookhagen, 2017;Wessel et al, 2018). Our correction steps do not seek to eliminate bias related to terrain characteristics at the scale of a few hundred meters, but rather to correct large scale biases related to primarily the SRTM-C at scales of several hundred meters to kilometers.…”

Section: Necessity Of Correction Stepsmentioning

confidence: 99%

“…TanDEM X-band and SRTM C-band radar have different penetration depths in dense vegetation (Carabajal and Harding, 2006;Hofton et al, 2006;Wessel et al, 2018) and snow and ice (Rignot et al, 2001;Rossi et al, 2016), leading to different height returns. We note this important caveat, but are able to ignore it for our particular study question (land-level change of bare material) and area (only partial vegetation and no permanent snow and ice).…”

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confidence: 99%

“…Terrain slope-also related to relief (Fig. S7)-is the primary cause of error in any DEM, demonstrated in the division of vertical uncertainties for most DEMs into slope bins (e.g., Wessel et al, 2018). Slope dependent errors may be reduced with higher resolution data and increased look angles for mosaicking, as in the case of TanDEM-X, but these uncertainties are expected to 20 remain as the most prevalent cause of error in any spaceborne DEM.…”

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confidence: 99%

“…Given the excellent agreement with differential GPS globally (Wessel et al, 2018) and in the study area (Purinton and Bookhagen, 2017) along with the minimal errors associated with orbital characteristics, we consider the TanDEM-X DEM as our reference surface in order to correct the more problematic SRTM-C. During correction, we do not apply any speckle reduction (e.g., via an adaptive filter as in Yamazaki et al (2017)), as we are interested in raw elevation values and not a smoothed DEM.…”

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confidence: 99%

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Measuring Decadal Vertical Land-level Changes from SRTM-C (2000) and TanDEM-X (~ 2015) in the South-Central Andes

Purinton¹,

Bookhagen²

2018

Preprint

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Abstract.Vertical change is often measured in the cryosphere via digital elevation model (DEM) differencing to assess glacier and icesheet mass balances. This requires the signal of change to outweigh the noise associated with the datasets. On the ice-free earth, land-level change is much smaller in magnitude and thus requires more accurate DEMs for differencing and identification of change. Previously, this has required high-resolution data at small scales. For the first time we measure land-level changes at the 5 scale of entire mountain belts in the south-central Andes using the SRTM-C (collected in 2000) and the TanDEM-X (collected from 2010-2015), both spaceborne radar DEMs. Long-standing errors in the SRTM-C are corrected using the TanDEM-X as a control surface and applying cosine-fit co-registration to remove~1/10 pixel (~3 m) shifts, Fast Fourier Transform and filtering to remove SRTM-C short-and long-wavelength stripes, and blocked shifting to remove remaining complex biases.The datasets are then differenced and outlier pixels are identified as potential signal for the case of gravel-bed channels and 10 hillslopes. We are able to identify signals of incision and aggradation (with magnitudes down to~3 m in best case) in two > 100 km river reaches, with increased geomorphic activity downstream of knickpoints. Anthropogenic gravel excavation and piling is prominently measured, with magnitudes exceeding ±5 m (up to > 10 m for large piles). These values correspond to conservative rates of 0.2 to > 0.5 m/yr for vertical changes in gravel-bed rivers. For hillslopes, since we require stricter cutoffs for noise, we are only able to identify one major landslide with a deposit volume of 16±0.15×10 change can be garnered from TanDEM-X auxiliary layers, however, these are more difficult to quantify. The methods presented can be extended to any region of the world with SRTM-C and TanDEM-X coverage where vertical land-level changes are of interest, with the caveat that remaining vertical uncertainties in primarily the SRTM-C limit detection in steep and complex topography.

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