Which DEM is best for analyzing fluvial landscape development in mountainous terrains?

Boulton, Sarah J.; Stokes, Martin

doi:10.1016/j.geomorph.2018.03.002

Cited by 148 publications

(88 citation statements)

References 80 publications

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“…This outcome hampers the applicability of the SRTM and TanDEM-X data in very detailed geomorphological research of the study area. Similar accuracy issues were observed in other areas with extremely rugged terrain [31,67].…”

Section: Discussionsupporting

confidence: 81%

“…The resulting DEM with a spatial resolution of 0.5 m provides a valuable dataset for mapping of any geomorphologic forms and terrain effects of dynamic geomorphologic process in this area. This product is also suitable for multiscale land surface analysis and segmentation [67]. The nested hierarchy of landforms and land surface processes can be captured only by a very accurate, complete, and spatially consistent DEM from which credible geomorphometric variables can be derived.…”

Section: Discussionmentioning

confidence: 99%

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Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

et al. 2019

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Airborne and terrestrial laser scanning and close-range photogrammetry are frequently used for very high-resolution mapping of land surface. These techniques require a good strategy of mapping to provide full visibility of all areas otherwise the resulting data will contain areas with no data (data shadows). Especially, deglaciated rugged alpine terrain with abundant large boulders, vertical rock faces and polished roche-moutones surfaces complicated by poor accessibility for terrestrial mapping are still a challenge. In this paper, we present a novel methodological approach based on a combined use of terrestrial laser scanning (TLS) and close-range photogrammetry from an unmanned aerial vehicle (UAV) for generating a high-resolution point cloud and digital elevation model (DEM) of a complex alpine terrain. The approach is demonstrated using a small study area in the upper part of a deglaciated valley in the Tatry Mountains, Slovakia. The more accurate TLS point cloud was supplemented by the UAV point cloud in areas with insufficient TLS data coverage. The accuracy of the iterative closest point adjustment of the UAV and TLS point clouds was in the order of several centimeters but standard deviation of the mutual orientation of TLS scans was in the order of millimeters. The generated high-resolution DEM was compared to SRTM DEM, TanDEM-X and national DMR3 DEM products confirming an excellent applicability in a wide range of geomorphologic applications.The general advantage of laser scanning over photogrammetry is in the ability of sampling several kinds of surfaces (e.g., top of vegetation canopy, inter-canopy surfaces, and ground) which are in the line of sight of the laser beam until impermeable surface restrains further penetration of the laser energy. UAV-SfM has become a low-cost alternative to TLS, generating point clouds with comparable accuracies to TLS albeit with the limitation of sampling the top surface in the field of view. Either way, in cases where TLS or UAV-SfM are used separately, data shadows originate in areas which are obscured in the sensor's field of view [23,29] (Figure 1). Complementing the unsampled areas with the surface altitude measurements is possible by sensing the area from multiple positions and different viewing perspectives by changing the location of the sensor. Zhang and Lin [30] provide a systematic overview of the lidar and photogrammetric data fusion. Cawood et al. [7] showed there is no exclusive method for capturing complex 3D geometry in the case study of 3D modelling a large boulder with distinct geological structural features. Combination of TLS and UAV-SfM provided the most satisfying results to capture the geometric complexity of the object of interest for structural analysis. A similar approach of combining different viewing geometry of TLS and photogrammetry was demonstrated in 3D modelling of a historical city by [23]. Planning the data collection in the mentioned studies concerned environments with a relatively easy access for the technology and the surveying pe...

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Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

et al. 2019

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“…The TanDEM-X 12 m DEM and intermediate DEM were found to be superior to SRTM and ASTER datasets in accuracy and landform identification [20,43,44] and when compared to ALOS in calculating geomorphometric parameters [45]. On the other hand, a comparison of DEMs for geomorphological analysis concluded that TanDEM-X 12 m produced drainage network errors in localized high-relief areas, despite its high vertical accuracy and resolution, and recommended the use of ALOS data based on its accurate drainage network and free availability [46].…”

Section: Related Workmentioning

confidence: 96%

Uncertainty in Catchment Delineations as a Result of Digital Elevation Model Choice

Keys

Baade

2019

Hydrology

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Nine digital elevation model (DEM) datasets were used for separate delineations of the Nam Co, Tibet catchment and its subcatchments, and these delineated areas were compared using the highest resolution dataset, TanDEM-X 12 m, as a baseline. The mean delineated catchment area was within 0.1% percent of the baseline delineation, with a standard error of the mean (SEM) that was 0.13% of the baseline. In a comparison of 49 subcatchment areas, TanDEM-X and ALOS datasets delineated similar areas, followed closely by SRTM 30 m, then SRTM 90 m, ACE2, and ASTER GDEM1. ASTER GDEM2 was a noteworthy outlier, having the largest mean subcatchment area that was nearly three times that of the baseline mean. Correlation coefficients were calculated for subcatchment parameters, SEM, and each DEM’s subcatchment area error. SEM had a weak but significant negative correlation with the mean and median slope. ASTER GDEM1 and GDEM2 were the only datasets that showed any significant correlations with the subcatchment environment variables, though these correlations were also weak. The 30 m posting ASTER GDEMs performed worse against the baseline than the other 30 m and 90 m datasets, showing that posting alone does not determine how good a dataset is. Our results show general small errors for catchment delineations, though there is the possibility for large errors, particularly in the older ASTER and SRTM datasets.

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“…Elevation Model with a resolution of 30 m from the Japan Aerospace Exploration Agency 210 (http://www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm) to perform the analysis following 211 recommendations of Boulton and Stokes (2018). Finally, we extract the average and standard 212 deviation ksn of each rock type using the digitised 1: 1 000 000 geological map of Morocco (Saadi et 213 al., 1985, see Supplementary Fig.…”

Section: River Profile Analysis Rock Type and Fluvial Erodibility 165mentioning

confidence: 99%

Rock strength and structural controls on fluvial erodibility: Implications for drainage divide mobility in a collisional mountain belt

Zondervan

Stokes

Boulton

et al. 2020

Earth and Planetary Science Letters

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Highlights 9• We estimate rock strength, erodibility and drainage divide mobility in the High Atlas 10Mountains 11• The weakest rock-type in the High Atlas is up to two orders of magnitude more erodible than 12 the strongest 13• In gently deformed horizontal strata of the sedimentary cover the drainage divide is mobile 14• Faulted and folded metamorphic sedimentary bedrock coincide with a stable drainage divide 15• Exhumation of crystalline basement forces the drainage divide into the centre of exposed 16 basement 17 Abstract 18 Numerical model simulations and experiments have suggested that when migration of the main 19 drainage divide occurs in a mountain belt, it can lead to the rearrangement of river catchments, 20 rejuvenation of topography, and changes in erosion rates and sediment flux. We assess the 21 progressive mobility of the drainage divide in three lithologically and structurally distinct groups of 22 bedrock in the High Atlas (NW Africa). The geological age of bedrock and its associated tectonic 23 architecture in the mountain belt increases from east to west in the study area, allowing us to 24 track both variations in rock strength and structural configuration which influence drainage 25 mobility during erosion through an exhuming mountain belt. Collection of field derived 26 measurements of rock strength using a Schmidt hammer and computer based extraction of river 27 channel steepness permit estimations of contrasts in fluvial erodibilities of rock types. The 28 resulting difference in fluvial erodibility between the weakest and the strongest lithological unit is 29 up to two orders of magnitude. Published evidence of geomorphic mobility of the drainage divide 30 indicates that such a range in erodibilities in horizontal stratigraphy of the sedimentary cover may 31 lead to changes in erosion rates as rivers erode through strata, leading to drainage divide 32 migration. In contrast, we show that the faulted and folded metamorphic sedimentary rocks in the 33 centre of the mountain belt coincide with a stable drainage divide. Finally, where the strong 34 igneous rocks of the crystalline basement are exposed after erosion of the covering meta-35 sediments, there is a decrease in fluvial erodibility of up to a factor of three, where the drainage 36 divide is mobile towards the centre of the exposed crystalline basement. The mobility of the 37 drainage divide in response to erosion through rock-types and their structural configuration in a 38 mountain belt has implications for the perception of autogenic dynamism of drainage networks 39 and fluvial erosion in mountain belts, and the interpretation of the geomorphology and 40 downstream stratigraphy. 41 42

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Which DEM is best for analyzing fluvial landscape development in mountainous terrains?

Cited by 148 publications

References 80 publications

Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

Uncertainty in Catchment Delineations as a Result of Digital Elevation Model Choice

Rock strength and structural controls on fluvial erodibility: Implications for drainage divide mobility in a collisional mountain belt

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