A Global Assessment of the SRTM Performance

Rodríguez, Ernesto; Morris, C. S.; Belz, J.

doi:10.14358/pers.72.3.249

Cited by 914 publications

(610 citation statements)

References 7 publications

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“…COMrisk Report (Kystdirektoratet, 2004) Coastal compared to previously reported estimates (Rodríguez et al, 2006) since SRTM accuracy has improved since then. An important artefact introduced by the SRTM relates to the fact that the 100 m resolution does not resolve the dune profile; therefore the coastal protection in the study area is underestimated.…”

Section: Digital Elevation Modelmentioning

confidence: 80%

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policymaking, and harmonization of climate change adaptation strategies. There is, however, limited insight into the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the coastal flood risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea level (ESL), (ii) the underlying uncertainty in the digital elevation model (DEM), (iii) flood defence information, (iv) the assumptions behind the use of depth-damage functions that express vulnerability, and (v) different climate change projections. The impact of these uncertainties on estimated expected annual damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal, and on the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, and their absolute and relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large datasets with sufficient resolution and accuracy, the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

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Section: Digital Elevation Modelmentioning

confidence: 80%

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…Many glacier elevation change studies have used this as a base dataset to compare to both newer and older data products (Rignot et al, 2003;Berthier et al, 2004;Larsen et al, 2007;Schiefer et al, 2007;Paul and Haeberli, 2008). Typically reported vertical uncertainties of the dataset are ≈ ±10 m which is lower than the mission standards of ±16 m (Rodriguez et al, 2006). However, vertical biases are present due to instability of the sensor and/or platform (Rabus et al, 2003), and elevation-dependent biases have also been shown due to penetration of the C-band radar waves (center frequency at 5.3 GHz) into snow and ice (Rignot et al, 2001;Berthier et al, 2006).…”

Section: Interferometric Srtm Demmentioning

confidence: 99%

“…This may be accomplished by minimizing stable terrain elevation residuals using a 2-D linear regression, e.g. iteratively shifting one DEM to the other within a ±5 pixel window (Rodriguez et al, 2006;Berthier et al, 2007;Howat et al, 2008). Other studies have corrected DEMs using single or multiple linear regression corrections between elevation and the location and terrain parameters (Gorokhovich and Voustianiouk, 2006;Bolch et al, 2008;Peduzzi et al, 2010).…”

mentioning

confidence: 99%

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011

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Abstract.There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the backlooking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

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“…The SRTM DEM of Kerguelen Islands (downloaded from ftp:// e0srp01u.ecs.nasa.gov, SRTM3, version 2) is characterized by a small percentage of data voids ($1%). Although SRTM is a global product, previous studies reported some significant regional differences in its accuracy [Berthier et al, 2006;Rodriguez et al, 2006;Surazakov and Aizen, 2006]. Thus, SRTM errors need to be determined on stable ice-free land before any glaciological application.…”

Section: Srtm Dem and Icesat Elevation Profilesmentioning

confidence: 99%

Ice wastage on the Kerguelen Islands (49°S, 69°E) between 1963 and 2006

Berthier¹,

Bris²,

Mabileau³

et al. 2009

J. Geophys. Res.

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International audienceWe observed the wastage of ice masses on the Kerguelen Islands (Indian Ocean, 49°S, 69°E) using historical information and recent satellite data. Overall, the total ice-covered area on the islands declined from 703 to 552 km2 between 1963 and 2001, a reduction of 21%. The area of Cook ice cap (the main ice body) decreased asymmetrically from 501 to 403 km2. West-flowing glaciers lost 11% of their area while east-flowing glaciers lost 28%. After 1991, the retreat rate accelerated from 1.9 km2/yr (1963-1991) to 3.8 km2/yr (1991-2003). Between 1963 and 2000, the ice volume loss was 25-30 km3, equivalent to an area-average ice thinning rate of 1.4-1.7 m/yr. The glacial retreat took place in the climatic context of a relatively low level of precipitation (compared to the 1950s) and a ~1°C warming that occurred between 1964 and 1982. The acceleration of the ice losses since, at least, the 1990s indicates that the state of the ice bodies on the Kerguelen Islands is still far from balanced. Together with other studies in Patagonia, South Georgia and Heard Island, our analysis is consistent with a pattern of strong and accelerated wastage of ice masses influenced by the Southern Ocean

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A Global Assessment of the SRTM Performance

Cited by 914 publications

References 7 publications

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

Ice wastage on the Kerguelen Islands (49°S, 69°E) between 1963 and 2006

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