scholarly journals Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

2017 ◽  
Vol 5 (2) ◽  
pp. 211-237 ◽  
Author(s):  
Benjamin Purinton ◽  
Bodo Bookhagen
Keyword(s):  
Standard Deviation ◽  
Profile Analysis ◽  
Digital Elevation Models ◽  
Frequency Noise ◽  
Differential Gps ◽  
Fourier Frequency ◽  
Digital Elevation ◽  
Southern Central ◽  
Standard Deviations ◽  
Terrain Elevation

Abstract. In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5 m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000 m of elevation. For the 30 m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12 m TanDEM-X and 5 m ALOS World 3D having < 2 m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10 m DEMs and the 30 m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30 m SRTM-C, 12–30 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X, and 5 m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m∕n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5 m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.

scholarly journals Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

2017 ◽  
Author(s):  
Benjamin Purinton ◽  
Bodo Bookhagen
Keyword(s):  
High Performance ◽  
Digital Elevation Models ◽  
Frequency Noise ◽  
Differential Gps ◽  
Fourier Frequency ◽  
Digital Elevation ◽  
Southern Central ◽  
Vertical Accuracy ◽  
C 30 ◽  
Terrain Elevation

Abstract. We validate and compare elevation accuracy and geomorphic metrics of the current generation of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km, and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, the SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X / TanDEM-X DEMs, and 5 m ALOS World 3D. We assessed vertical accuracy by comparing standard deviations (SD) of the DEM elevation versus 307,509 differential GPS (dGPS) measurements across 4,000 m of elevation. Vertical SD for the 30 m DEMs were 9.48 m (ASTER GDEM2), 6.93 m (ASTER Stack), 3.33 m (SRTM-C), 2.81 m (ALOS World 3D), and 2.42 m (TanDEM-X). Values were generally lower for higher resolution DEMs at 2.02–3.83 m (10 m single-CoSSC TerraSAR-X / TanDEM-X), 1.97 m (12 m TanDEM-X), and 1.64 m (5 m ALOS World3D). Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the high performance across these attributes of the 30 m SRTM-C, 30 m and 12 m TanDEM-X, and 30 m and 5 m ALOS World 3D DEMs. Single-CoSSC TerraSAR-X / TanDEM-X 10 m DEMs and the 30 m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on high vertical accuracy and visual inspection of minimal hillslope artifacts alongside optical satellite data, we selected the 30 m SRTM-C, 12–30 m TanDEM-X, 10 m single-CoSSC TerraSAR-X / TanDEM-X, and 5 m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. For trunk channel profiles analyzed with chi plots, consistent m/n values of 0.49–0.57 were found regardless of DEM resolution or SD. Hillslopes were compared through slope and curvature calculations to assess basin-wide differences in their distributions and in the hillslope-to-valley transition related to the knickpoint feature. We find 0.1–0.2 m/m higher slopes downstream of the knickpoint, related to the over-steepened baselevel. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5 m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data is still necessary for meter-scale analysis.

scholarly journals Accuracy Evaluation of Four Greenland Digital Elevation Models (DEMs) and Assessment of River Network Extraction

2020 ◽  
Vol 12 (20) ◽  
pp. 3429
Author(s):  
Ziyang Xing ◽  
Zhaohui Chi ◽  
Ying Yang ◽  
Shiyi Chen ◽  
Huabing Huang ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Digital Elevation Models ◽  
Greenland Ice Sheet ◽  
River Network ◽  
The Other ◽  
Time Range ◽  
Accuracy Evaluation ◽  
Digital Elevation ◽  
Dem Accuracy ◽  
The Impact

Digital Elevation Models (DEMs) of Greenland provide the basic data for studying the Greenland ice sheet (GrIS), but little research quantitatively evaluates and compares the accuracy of various Greenland DEMs. This study uses IceBridge elevation data to evaluate the accuracies of the the Greenland Ice Map Project (GIMP)1 DEM, GIMP2 DEM, TanDEM-X, and ArcticDEM in their corresponding time ranges. This study also analyzes the impact of DEM accuracy and resolution on the accuracy of river network extraction. The results show that (1) within the time range covered by each DEM, TanDEM-X with an RMSE of 5.60 m has higher accuracy than the other DEMs in terms of absolute height accuracy, while GIMP1 has the lowest accuracy among the four Greenland DEMs, with an RMSE of 14.34 m. (2) Greenland DEMs are affected by regional errors and interannual changes. The accuracy in areas with elevations above 2000 m is higher than that in areas with elevations below 2000 m, and better accuracy is observed in the north than in the south. The stability of the ArcticDEM product is higher than those of the other three DEM products, and its RMSE standard deviation over multiple years is only 0.14 m. Therefore, the errors caused by the applications of DEMs with longer time spans are smaller. GIMP1 performs in an opposite manner, with a standard deviation of 2.39 m. (3) The river network extracted from TanDEM-X is close to the real river network digitized from remote sensing images, with an accuracy of 50.78%. The river network extracted from GIMP1 exhibits the largest errors, with an accuracy of only 8.83%. This study calculates and compares the accuracy of four Greenland DEMs and indicates that TanDEM-X has the highest accuracy, adding quantitative studies on the accuracy evaluation of various Greenland DEMs. This study also compares the results of different DEM river network extractions, verifies the impact of DEM accuracy on the accuracy of the river network extraction results, and provides an explorable direction for the hydrological analysis of Greenland as a whole.

scholarly journals Introducing QuickChi, a web application for near-global, exploratory, longitudinal river profile analysis

2021 ◽  
Author(s):  
Gregory Ruetenik
Keyword(s):  
Steady State ◽  
Open Source ◽  
Web Application ◽  
Profile Analysis ◽  
Digital Elevation Models ◽  
Global Scale ◽  
Exploratory Analysis ◽  
Tectonic Geomorphology ◽  
The Past ◽  
Digital Elevation

Stream profile analysis has been used extensively in the field of tectonic geomorphology. In the past, exploration of stream profiles, including χ-elevation profiles, has required downloading and processing Digital Elevation Models for specific areas, which limits the scope of exploratory analysis. Presented here is a web application designed to analyze stream profiles at 90m resolution at a near-global scale. Based on the Hydrosheds (Wickel et al., 2007) 90m drainage direction, as well as computed d8 drainage direction and void-filled DEMs, the app allows users to quickly query downstream from selected points anywhere within ±60 degrees latitude, in order to interactively analyze corresponding stream profiles in both distance and χ space, where χ is a metric that is proportional to the presumed steady-state shape of the stream profile (Perron and Royden, 2013). QuickChi is open source, and although currently it is designed as an exploratory tool, more functions can be easily added via community contributions and/or from existing toolsets.

scholarly journals Elevation changes of glaciers revealed by multitemporal digital elevation models calibrated by GPS survey in the Khumbu region, Nepal Himalaya, 1992-2008

2012 ◽  
Vol 58 (210) ◽  
pp. 648-656 ◽  
Author(s):  
Takayuki Nuimura ◽  
Koji Fujita ◽  
Satoru Yamaguchi ◽  
Rishi R. Sharma
Keyword(s):  
Digital Elevation Models ◽  
Weighted Least Squares ◽  
High Mountain ◽  
Elevation Change ◽  
Remotely Sensed Data ◽  
Differential Gps ◽  
Nepal Himalaya ◽  
Gps Survey ◽  
Digital Elevation ◽  
Elevation Changes

AbstractDue to remoteness and high altitude, only a few ground-based glacier change studies are available in high-mountain areas in the Himalaya. However, digital elevation models based on remotely sensed data (RS-DEMs) provide feasible opportunities to evaluate how fast Himalayan glaciers are changing. Here we compute elevation changes in glacier surface (total area 183.3 km2) in the Khumbu region, Nepal Himalaya, for the period 1992-2008 using multitemporal RS-DEMs and a map-derived DEM calibrated with differential GPS survey data in 2007. Elevation change is calculated by generating a weighted least-squares linear regression model. Our method enables us to provide the distribution of uncertainty of the elevation change. Debris-covered areas show large lowering rates. The spatial distribution of elevation change shows that the different wastage features of the debris-covered glaciers depend on their scale, slope and the existence of glacial lakes. The elevation changes of glaciers in the eastern Khumbu region are in line with previous studies. The regional average mass balance of -0.40 ± 0.25 m w.e.a-1 for the period 1992-2008 is consistent with a global value of about -0.55 m w.e. a-1 for the period 1996-2005.

scholarly journals Quality Assessment and Glaciological Applications of Digital Elevation Models Derived from Space-Borne and Aerial Images over Two Tidewater Glaciers of Southern Spitsbergen

2019 ◽  
Vol 11 (9) ◽  
pp. 1121 ◽  
Author(s):  
Małgorzata Błaszczyk ◽  
Dariusz Ignatiuk ◽  
Mariusz Grabiec ◽  
Leszek Kolondra ◽  
Michał Laska ◽  
...  
Keyword(s):  
Mass Balance ◽  
Digital Elevation Models ◽  
Control Point ◽  
Aerial Photographs ◽  
Differential Gps ◽  
Tidewater Glaciers ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Elevation Changes ◽  
Geodetic Mass Balance

In this study, we assess the accuracy and precision of digital elevation models (DEM) retrieved from aerial photographs taken in 2011 and from Very High Resolution satellite images (WorldView-2 and Pléiades) from the period 2012–2017. Additionally, the accuracy of the freely available Strip product of ArcticDEM was verified. We use the DEMs to characterize geometry changes over Hansbreen and Hornbreen, two tidewater glaciers in southern Spitsbergen, Svalbard. The satellite-based DEMs from WorldView-2 and Pléiades stereo pairs were processed using the Rational Function Model (RFM) without and with one ground control point. The elevation quality of the DEMs over glacierized areas was validated with in situ data: static differential GPS survey of mass balance stakes and GPS kinematic data acquired during ground penetrating radar survey. Results demonstrate the usefulness of the analyzed sources of DEMs for estimation of the total geodetic mass balance of the Svalbard glaciers. DEM accuracy is sufficient to investigate glacier surface elevation changes above 1 m. Strips from the ArcticDEM are generally precise, but some of them showed gross errors and need to be handled with caution. The surface of Hansbreen and Hornbreen has been lowering in recent years. The average annual elevation changes for Hansbreen were more negative in the period 2015–2017 (−2.4 m a−1) than in the period 2011–2015 (−1.7 m a−1). The average annual elevation changes over the studied area of Hornbreen for the period 2012–2017 amounted to −1.6 m a−1. The geodetic mass balance for Hansbreen was more negative than the climatic mass balance estimated using the mass budget method, probably due to underestimation of the ice discharge. From 2011 to 2017, Hansbreen lost on average over 1% of its volume each year. Such a high rate of relative loss illustrates how fast these glaciers are responding to climate change.

scholarly journals EVALUATING THE EFFECTS OF REDUCTIONS IN LiDAR DATA ON THE VISUAL AND STATISTICAL CHARACTERISTICS OF THE CREATED DIGITAL ELEVATION MODELS

2016 ◽  
Vol III-2 ◽  
pp. 91-98 ◽  
Author(s):  
F. F. Asal
Keyword(s):  
Point Cloud ◽  
Digital Elevation Models ◽  
Statistical Characteristics ◽  
Lidar Data ◽  
High Point ◽  
Digital Elevation ◽  
Data Density ◽  
Standard Deviations ◽  
Dem Accuracy ◽  
Data Reductions

With continuous developments in LiDAR technologies high point cloud densities have been attainable but accompanied by challenges for processing big volumes of data. Reductions in high point cloud densities are expected to lower data acquisition and data processing costs; however this could affect the characteristics of the generated Digital Elevation Models (DEMs). This research aimed to evaluate the effects of reductions in airborne LiDAR point cloud data densities on the visual and statistical characteristics of the generated DEMs. DEMs have been created from a dataset which constitutes last returns of raw LiDAR data that was acquired at bare lands for Gilmer County, USA between March and April 2004, where qualitative and quantitative testing analyses have been performed. Visual analysis has shown that the DEM can withstand a considerable degree of quality with reduced densities down to 0.128&thinsp;pts/m<sup>2</sup> (47&thinsp;% of the data remaining), however degradations in the DEM visual characteristics appeared in coarser tones and rougher textures have occurred with more reductions. Additionally, the statistical analysis has indicated that the standard deviations of the DEM elevations have decreased by only 22&thinsp;% of the total decrease with data density reductions down to 0.101&thinsp;pts/m<sup>2</sup> (37&thinsp;% of the data remaining) while greater rate of decreasing in the standard deviations has occurred with more reductions referring to greater rate of surface smoothing and elevation approximating. Furthermore, the accuracy analysis testing has given that the DEM accuracy has degraded by only 4.83&thinsp;% of the total degradations with data density reductions down to 0.128&thinsp;pts/m<sup>2</sup>, however great deteriorations in the DEM accuracy have occurred with more data reductions. Finally, it is recommended that LiDAR data can withstand point density reductions down to 0.128&thinsp;pts/m<sup>2</sup> (about 50&thinsp;% of the data) without big deteriorations in the visual and statistical characteristics of the generated DEMs.

scholarly journals EVALUATING THE EFFECTS OF REDUCTIONS IN LiDAR DATA ON THE VISUAL AND STATISTICAL CHARACTERISTICS OF THE CREATED DIGITAL ELEVATION MODELS

2016 ◽  
Vol III-2 ◽  
pp. 91-98 ◽  
Author(s):  
F. F. Asal
Keyword(s):  
Point Cloud ◽  
Digital Elevation Models ◽  
Statistical Characteristics ◽  
Lidar Data ◽  
High Point ◽  
Digital Elevation ◽  
Data Density ◽  
Standard Deviations ◽  
Dem Accuracy ◽  
Data Reductions

With continuous developments in LiDAR technologies high point cloud densities have been attainable but accompanied by challenges for processing big volumes of data. Reductions in high point cloud densities are expected to lower data acquisition and data processing costs; however this could affect the characteristics of the generated Digital Elevation Models (DEMs). This research aimed to evaluate the effects of reductions in airborne LiDAR point cloud data densities on the visual and statistical characteristics of the generated DEMs. DEMs have been created from a dataset which constitutes last returns of raw LiDAR data that was acquired at bare lands for Gilmer County, USA between March and April 2004, where qualitative and quantitative testing analyses have been performed. Visual analysis has shown that the DEM can withstand a considerable degree of quality with reduced densities down to 0.128&thinsp;pts/m&lt;sup&gt;2&lt;/sup&gt; (47&thinsp;% of the data remaining), however degradations in the DEM visual characteristics appeared in coarser tones and rougher textures have occurred with more reductions. Additionally, the statistical analysis has indicated that the standard deviations of the DEM elevations have decreased by only 22&thinsp;% of the total decrease with data density reductions down to 0.101&thinsp;pts/m&lt;sup&gt;2&lt;/sup&gt; (37&thinsp;% of the data remaining) while greater rate of decreasing in the standard deviations has occurred with more reductions referring to greater rate of surface smoothing and elevation approximating. Furthermore, the accuracy analysis testing has given that the DEM accuracy has degraded by only 4.83&thinsp;% of the total degradations with data density reductions down to 0.128&thinsp;pts/m&lt;sup&gt;2&lt;/sup&gt;, however great deteriorations in the DEM accuracy have occurred with more data reductions. Finally, it is recommended that LiDAR data can withstand point density reductions down to 0.128&thinsp;pts/m&lt;sup&gt;2&lt;/sup&gt; (about 50&thinsp;% of the data) without big deteriorations in the visual and statistical characteristics of the generated DEMs.

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