scholarly journals Vertical Accuracy of Freely Available Global Digital Elevation Models (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM)

2020 ◽  
Vol 12 (21) ◽  
pp. 3482
Author(s):  
Evelyn Uuemaa ◽  
Sander Ahi ◽  
Bruno Montibeller ◽  
Merle Muru ◽  
Alexander Kmoch

Freely available global digital elevation models (DEMs) are important inputs for many research fields and applications. During the last decade, several global DEMs have been released based on satellite data. ASTER and SRTM are the most widely used DEMs, but the more recently released, AW3D30, TanDEM-X and MERIT, are being increasingly used. Many researchers have studied the quality of these DEM products in recent years. However, there has been no comprehensive and systematic evaluation of their quality over areas with variable topography and land cover conditions. To provide this comparison, we examined the accuracy of six freely available global DEMs (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM) in four geographic regions with different topographic and land use conditions. We used local high-precision elevation models (Light Detection and Ranging (LiDAR), Pleiades-1A) as reference models and all global models were resampled to reference model resolution (1m). In total, 608 million 1x1 m pixels were analyzed. To estimate the accuracy, we generated error rasters by subtracting each reference model from the corresponding global DEM and calculated descriptive statistics for this difference (e.g., median, mean, root-mean-square error (RMSE)). We also assessed the vertical accuracy as a function of the slope, slope aspect, and land cover. We found that slope had the strongest effect on DEM accuracy, with no relationship for slope aspect. The AW3D30 was the most robust and had the most stable performance in most of the tests and is therefore the best choice for an analysis of multiple geographic regions. SRTM and NASADEM also performed well where available, whereas NASADEM, as a successor of SRTM, showed only slight improvement in comparison to SRTM. MERIT and TanDEM-X also performed well despite their lower spatial resolution.

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4865 ◽  
Author(s):  
Zhiwei Liu ◽  
Jianjun Zhu ◽  
Haiqiang Fu ◽  
Cui Zhou ◽  
Tingying Zuo

The global digital elevation model (DEM) is important for various scientific applications. With the recently released TanDEM-X 90-m DEM and AW3D30 version 2.2, the open global or near-global coverage DEM datasets have been further expanded. However, the quality of these DEMs has not yet been fully characterized, especially in the application for regional scale studies. In this study, we assess the quality of five freely available global DEM datasets (SRTM-1 DEM, SRTM-3 DEM, ASTER GDEM2, AW3D30 DEM and TanDEM-X 90-m DEM) and one 30-m resampled TanDEM-X DEM (hereafter called TDX30) over the south-central Chinese province of Hunan. Then, the newly-released high precision ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) altimetry points are introduced to evaluate the accuracy of these DEMs. Results show that the SRTM1 DEM offers the best quality with a Root Mean Square Error (RMSE) of 8.0 m, and ASTER GDEM2 has the worst quality with the RMSE of 10.1 m. We also compared the vertical accuracies of these DEMs with respect to different terrain morphological characteristics (e.g., elevation, slope and aspect) and land cover types. It reveals that the DEM accuracy decreases when the terrain elevation and slope value increase, whereas no relationship was found between DEM error and terrain aspect. Furthermore, the results show that the accuracy increases as the land cover type changes from vegetated to non-vegetated. Overall, the SRTM1 DEM, with high spatial resolution and high vertical accuracy, is currently the most promising dataset among these DEMs and it could, therefore, be utilized for the studies and applications requiring accurate DEMs.


2020 ◽  
Vol 12 (20) ◽  
pp. 3429
Author(s):  
Ziyang Xing ◽  
Zhaohui Chi ◽  
Ying Yang ◽  
Shiyi Chen ◽  
Huabing Huang ◽  
...  

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.


2020 ◽  
Vol 9 (11) ◽  
pp. 620
Author(s):  
Xiran Zhou ◽  
Xiao Xie ◽  
Yong Xue ◽  
Bing Xue ◽  
Kai Qin ◽  
...  

High-resolution digital elevation models (DEMs) and its derivatives (e.g., curvature, slope, aspect) offer a great possibility of representing the details of Earth’s surface in three-dimensional space. Previous research investigations concerning geomorphological variables and region-level features alone cannot precisely characterize the main structure of landforms. However, these geomorphological variables are not sufficient to represent a complex landform object’s whole structure from a high-resolution DEM. Moreover, the amount of the DEM dataset is limited, including the landform object. Considering the challenges above, this paper reports an integrated model called the bag of geomorphological words (BoGW), enabling automatic landform recognition via integrating point and linear geomorphological variables, region-based features (e.g., shape, texture), and high-level landform descriptions. First, BoGW semantically characterizes the composition of geomorphological variables and meaningful parcels of each type of landform. Based on a landform’s semantics, the proposed method then integrates geomorphological variables and region-level features (e.g., shape, texture) to create the feature vector for the landform. Finally, BoGW classifies a region derived from high-resolution DEM into a predefined type of landform by the feature vector. The experimental results on crater and cirque detection indicated that the proposed BoGW could support landform object recognition from high-resolution DEMs.


2020 ◽  
Vol 43 (8) ◽  
pp. 1939-1955
Author(s):  
Joanna Rotnicka ◽  
Maciej Dłużewski ◽  
Maciej Dąbski ◽  
Mirosław Rodzewicz ◽  
Wojciech Włodarski ◽  
...  

Abstract Recent developments in unmanned aerial vehicles (UAVs) have resulted in high-resolution digital elevation models (DEMs) of vulnerable coastal environments, including beach–foredune topography. If performed repetitively, they can offer an excellent tool to determine the spatial and temporal changes in the sediment budget, which may be required for proper land management. However, the quality of a UAV, slope parameters, and vegetation significantly influence DEM accuracy. The aim of this study is to compare precise GPS-RTK transects across a section of the South Baltic coast in Poland with those obtained from a DEM based on high-resolution and high-accuracy images obtained by a wind-resistant, high-quality fixed-wing UAV during beyond visual line of sight operation (BVLOS). Different land cover classes, slope inclination, and general curvature, as well as surface roughness, were taken into consideration as possible factors influencing the uncertainty. The study revealed that marram grass greatly affects the accuracy of the UAV-derived model and that the uncertainty of the UAV-derived DEM increases together with increasing slope inclination and, to a lesser degree, with increasing general slope curvature. We showed that sediment budget determinations with the use of a UAV-based DEM are correct only where grass cover is sparse, in our study, up to 20% of the area.


Author(s):  
L. Feng ◽  
J.-P. Muller

From the latest TanDEM-X mission (bistatic X-Band interferometric SAR), globally consistent Digital Elevation Model (DEM) will be available from 2017, but their accuracy has not yet been fully characterised. This paper presents the methods and implementation of statistical procedures for the validation of the vertical accuracy of TanDEM-X iDEMs at grid-spacing of approximately 12.5 m, 30 m and 90 m based on processed ICESat data over the UK in order to assess their potential extrapolation across the globe. The accuracy of the TanDEM-X iDEM in UK was obtained as follows: against ICESat GLA14 elevation data, TanDEM-X iDEM has −0.028±3.654 m over England and Wales and 0.316 ± 5.286 m over Scotland for 12 m, −0.073 ± 6.575 m for 30 m, and 0.0225 ± 9.251 m at 90 m. Moreover, 90 % of all results at the three resolutions of TanDEM-X iDEM data (with a linear error at 90 % confidence level) are below 16.2 m. These validation results also indicate that derivative topographic parameters (slope, aspect and relief) have a strong effect on the vertical accuracy of the TanDEM-X iDEMs. In high-relief and large slope terrain, large errors and data voids are frequent, and their location is strongly influenced by topography, whilst in the low- to medium-relief and low slope sites, errors are smaller. ICESat derived elevations are heavily influenced by surface slope within the 70 m footprint as well as there being slope dependent errors in the TanDEM-X iDEMs.


2019 ◽  
Vol 28 (1) ◽  
pp. 95-105 ◽  
Author(s):  
I. P. Kovalchuk ◽  
K. A. Lukianchuk ◽  
V. A. Bogdanets

The relief has a major impact on the landscape`s hydrological, geomorphological and biological processes. Many geographic information systems used elevation data as the primary data for analysis, modeling, etc. A digital elevation model (DEM) is a modern representation of the continuous variations of relief over space in digital form. Digital Elevation Models (DEMs) are important source for prediction of soil erosion parameters. The potential of global open source DEMs (SRTM, ASTER, ALOS) and their suitability for using in modeling of erosion processes are assessed in this study. Shumsky district of Ternopil region, which is located in the Western part of Ukraine, is the area of our study. The soils of Shumsky district are adverselyaffected by erosion processes. The analysis was performed on the basis of the characteristics of the hydrological network and relief. The reference DEM was generated from the hypsographic data(contours) on the 1:50000 topographical map series compiled by production units of the Main Department of Geodesy and Cartography under the Council of Ministers. The differences between the reference DEM and open source DEMs (SRTM, ASTER and ALOS) are examined. Methods of visual detection of DEM defects, profiling, correlation, and statistics were used in the comparative analysis. This research included the analysis oferrors that occurred during the generation of DEM. The vertical accuracy of these DEMs, root mean square error (RMSE), absolute and relative errors, maximum deviation, and correlation coefficient have been calculated. Vertical accuracy of DEMs has been assessed using actual heights of the sample points. The analysis shows that SRTM and ALOS DEMs are more reliable and accurate than ASTER GDEM. The results indicate that vertical accuracy of DEMs is 7,02m, 7,12 m, 7,60 mand 8,71 m for ALOS, SRTM 30, SRTM 90 and ASTER DEMs respectively. ASTER GDEM had the highest absolute, relative and root mean square errors, the highest maximum positive and negative deviation, a large difference with reference heights, and the lowest correlation coefficient. Therefore, ASTER GDEM is the least acceptable for studying the intensity and development of erosion processes. The use of global open source DEMs, compared with the vectorization of topographic maps,greatly simplifies and accelerates the modeling of erosion processes and the assessment of the erosion risk in the administrative district.


2017 ◽  
Vol 23 (4) ◽  
pp. 654-668 ◽  
Author(s):  
Josyceyla Duarte Morais ◽  
Thaísa Santos Faria ◽  
Marcos Antonio Timbó Elmiro ◽  
Marcelo Antonio Nero ◽  
Archibald de Araujo Silva ◽  
...  

Abstract: This work is an altimetry evaluation study involving Digital Elevation Models ASTER GDEM version 2 and SRTM version 3. Both models are readily available free of charge, however as they are built from different remote sensing methods it is also expected that they present different data qualities. LIDAR data with 25 cm vertical accuracy were used as reference for assessment validation. The evaluation study, carried out in urbanized area, investigated the distribution of the residuals and the relationship between the observed errors with land slope classes. Remote sensing principles, quantitative statistical methods and the Cartographic Accuracy Standard of Digital Mapping Products (PEC-PCD) were considered. The results indicated strong positive linear correlation and the existence of a functional relationship between the evaluated models and the reference model. Residuals between -4.36 m and 3.11 m grouped 47.7% of samples corresponding to ASTER GDEM and 63.7% of samples corresponding to SRTM. In both evaluated models, Root Mean Square Error values increased with increasing of land slope. Considering 1: 50,000 mapping scale the PEC-PCD classification indicated class B standard for SRTM and class C for ASTER GDEM. In all analyzes, SRTM presented smaller altimetry errors compared to ASTER GDEM, except in areas with steep relief.


Sign in / Sign up

Export Citation Format

Share Document