A Relief Dependent Evaluation of Digital Elevation Models on Different Scales for Northern Chile

Kramm, Tanja; Hoffmeister, Dirk

doi:10.3390/ijgi8100430

Cited by 24 publications

(9 citation statements)

References 95 publications

(137 reference statements)

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“…The choices can be overwhelming, and deficiencies continue to plague global DEMs (Hawker et al, 2018;Schumann and Bates, 2018;Polidori and El Hage, 2020). This has led to many calibration and validation studies for these products, with the goal of assessing their absolute elevation accuracy through reference measurements (e.g., Rodríguez et al, 2006;Tachikawa et al, 2011;Rexer and Hirt, 2014;Baade and Schmullius, 2016;Becek et al, 2016;Wessel et al, 2018;Kramm and Hoffmeister, 2019), and, less often, their geomorphic suitability (Pipaud et al, 2015;Purinton and Bookhagen, 2017;Schwanghart and Scherler, 2017;Boulton and Stokes, 2018;Grohmann, 2018). Accuracy is often expressed by statistical analysis of multiple measurements carried out at the individual point or pixel level from sparse differential GNSS (dGNSS) or other reference data (e.g., ICESat or ICESat-2; Carabajal and Harding, 2006;Neuenschwander and Pitts, 2019;Carabajal and Boy, 2020).…”

Section: Introductionmentioning

confidence: 99%

Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes

Purinton

Bookhagen

2021

Front. Earth Sci.

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Quantitative geomorphic research depends on accurate topographic data often collected via remote sensing. Lidar, and photogrammetric methods like structure-from-motion, provide the highest quality data for generating digital elevation models (DEMs). Unfortunately, these data are restricted to relatively small areas, and may be expensive or time-consuming to collect. Global and near-global DEMs with 1 arcsec (∼30 m) ground sampling from spaceborne radar and optical sensors offer an alternative gridded, continuous surface at the cost of resolution and accuracy. Accuracy is typically defined with respect to external datasets, often, but not always, in the form of point or profile measurements from sources like differential Global Navigation Satellite System (GNSS), spaceborne lidar (e.g., ICESat), and other geodetic measurements. Vertical point or profile accuracy metrics can miss the pixel-to-pixel variability (sometimes called DEM noise) that is unrelated to true topographic signal, but rather sensor-, orbital-, and/or processing-related artifacts. This is most concerning in selecting a DEM for geomorphic analysis, as this variability can affect derivatives of elevation (e.g., slope and curvature) and impact flow routing. We use (near) global DEMs at 1 arcsec resolution (SRTM, ASTER, ALOS, TanDEM-X, and the recently released Copernicus) and develop new internal accuracy metrics to assess inter-pixel variability without reference data. Our study area is in the arid, steep Central Andes, and is nearly vegetation-free, creating ideal conditions for remote sensing of the bare-earth surface. We use a novel hillshade-filtering approach to detrend long-wavelength topographic signals and accentuate short-wavelength variability. Fourier transformations of the spatial signal to the frequency domain allows us to quantify: 1) artifacts in the un-projected 1 arcsec DEMs at wavelengths greater than the Nyquist (twice the nominal resolution, so > 2 arcsec); and 2) the relative variance of adjacent pixels in DEMs resampled to 30-m resolution (UTM projected). We translate results into their impact on hillslope and channel slope calculations, and we highlight the quality of the five DEMs. We find that the Copernicus DEM, which is based on a carefully edited commercial version of the TanDEM-X, provides the highest quality landscape representation, and should become the preferred DEM for topographic analysis in areas without sufficient coverage of higher-quality local DEMs.

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Section: Introductionmentioning

confidence: 99%

Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes

Purinton

Bookhagen

2021

Front. Earth Sci.

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“…There has been some research on the quality assessment of TanDEM-X IDEM and the final TanDEM-X DEM product. The research used RTK-GNSS ground measurement points [20], ICESat data [21], globally distributed GPS points [22], local DEMs [23], LiDAR DEM [24] or high-quality DSM derived from small footprint airborne LiDAR [25] as the reference data to assess the vertical accuracy of TanDEM-X IDEM [20,23] or TanDEM-X DEM [21,22,24,25] globally [21,22] or in local study area [20,[23][24][25] with different altitudes, topography and vegetation [26][27][28][29][30][31][32]. The researchers also compared the obtained accuracy with other DEMs such as SRTM and ASTER GDEM.…”

Section: Introductionmentioning

confidence: 99%

Quality Assessment of TanDEM-X DEMs, SRTM and ASTER GDEM on Selected Chinese Sites

2021

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Digital elevation models (DEMs) are the basic data of science and engineering technology research. SRTM and ASTER GDEM are currently widely used global DEMs, and TanDEM-X DEM, released in 2016, has attracted users’ attention due to its unprecedented accuracy. These global datasets are often used for local applications and the quality of DEMs affects the results of applications. Many researchers have assessed and compared the quality of global DEMs on a local scale. To provide some additional insights on quality assessment of 12- and 30-m resolution TanDEM-X DEMs, 30-m resolution ASTER GDEM and 30-m resolution SRTM, this study assessed differences’ performance in relation to not only geographical features but also the ways in which DEMs have been created on selected Chinese sites, taking ICESat/GLAS points with 14-cm absolute vertical accuracy but size of 70-m diameter and 12-m resolution TanDEM-X DEM with less than 10-m absolute vertical accuracy as the reference data for comprehensive quality evaluation. When comparing the three 30-m DEMs with the reference DEM, an improved Least Z-Difference (LZD) method was applied for co-registration between models, and Quantile–Quantile (Q-Q) plot was used to identify if the DEM errors follow a normal distribution to help choose proper statistical indicators accordingly. The results show that: (1) TanDEM-X DEMs have the best overall quality, followed by SRTM. ASTER GDEM has the worst quality. The 12-m TanDEM-X DEM has significant advantages in describing terrain details. (2) The quality of DEM has a strong relationship with slope, aspect and land cover. However, the relationship between aspect and vertical quality weakens after data co-registration. The quality of DEMs gets higher with the increasing number of images used in the fusion process. The quality in where slopes opposite to the radar beam is the worst for SRTM, which could provide a new perspective for quality assessment of SRTM and other DEMs whose incidence angle files are available. (3) Systematic deviations can reduce the vertical quality of DEM. The differences have non-normal distribution even after co-registration. For researchers who want to know the quality of a DEM in order to use it in further applications, they should pay more attention to the terrain factors and land cover in their study areas and the ways in which the DEM has been created.

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“…Podgórski et al [58] 2019 assessed the accuracy for different slopes. Kramm and Hoffmeister [59] calculated topographic roughness index for multiple sourced DEMs including UAV generated data.…”

Section: Discussionmentioning

confidence: 99%

Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

Chaudhry

Ahmad

Gulzar

2020

IJGI

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Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.

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A Relief Dependent Evaluation of Digital Elevation Models on Different Scales for Northern Chile

Cited by 24 publications

References 95 publications

Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes

Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes

Quality Assessment of TanDEM-X DEMs, SRTM and ASTER GDEM on Selected Chinese Sites

Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling

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