Special Issue "Advances in Global Digital Elevation Model Processing"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 30 September 2021.

Special Issue Editors

Dr. Tomaž Podobnikar
E-Mail Website
Guest Editor
Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova 2, SI-1000 Ljubljana, Slovenia
Interests: spatial analysis; geomorphometry; DEM; DTM; GIS; remote sensing; geovisual analytics; spatial data quality; image processing; spatial generalization; spatial data integration; spatial statistics; (palaeo)environmental analysis; landscape archaeology; natural hazard
Special Issues and Collections in MDPI journals
Prof. Dr. Juha Oksanen
E-Mail Website
Guest Editor
Department of Geoinformatics and Cartography, Finnish Geospatial Research Institute in the National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland
Interests: DEM; DTM; high-performance geocomputing; uncertainty-aware geospatial analysis; interactive map design; geovisual analytics; spatial data infrastructures

Special Issue Information

Dear Colleagues,

The topographic features of our Earth have always been the key to our orientation in geographic space. A digital elevation model (DEM) is a powerful surface model of the Earth or of any other planets. It can provide explicate and more inherently hidden information of the topographic complexity, in a simplified way. DEM is promising for various applications in the broader wider field of geoscience, engineering, and virtual reality, as well as in natural, environmental and social sciences, and even in entertainment. A relevant global DEM plays a role in the connectivity of our society.

At present, a number of terrestrial and bathymetric global DEMs can be obtained. They can be commercial, with a typical horizontal resolution of around 10 m, or under free licenses or public domain, with resolution of around 30 m (e.g., SRTM, GMTED, ASTER GDEM, AW3D, and ETOPO). In addition to these, there are a number of freely available DEMs in regional (e.g., EU-DEM and ArcticDEM) and national scales. Most DEMs are actually digital surface models (DSMs), which include the tops of buildings, vegetation cover, temporal snow cover, and so on. However, digital terrain models (DTMs) with pure bare Earth are mostly required by users.

The key research questions are as follows: “Which elements can improve the usability of freely available global DEMs?” and, closely linked, “How can we improve such DEMs’ quality when using geomorphometric methods?”. This Issue is fundamental in order to ensure the best performance of any spatial analysis involving DEM and for reducing uncertainties.

The authors are invited to explore any of the following related critical topics, but are not only limited to these. Firstly, is it possible to involve a geomorphometry in automatic DEM quality improvement, bearing in mind the relevant experiences in order to determine the remarkable geomorphological features, which are, let us say five-times more detailed than the grid size? The issues are the vertical positional accuracy, temporal and conceptual consistency, and details without any artefacts. Because a more detailed DEM usually contains other kinds of errors and uncertainties, the question is, if it is more important to have a high spatial resolution DEM with noises, or to have an overall consistent DEM in an optimal scale. In fact, an optimal scale is usually a multi-scale DEM, where the choice of a particular scale can significantly depend on the processing time of the selected spatial analysis of these massive datasets. There is a need to associate geometrical, geomorphological, and semantical aspects in DEM processing. As there are already a number of global and other DEM datasets available, the question is whether the geomorphometric methods can be used to harmonize them with integration, fusion, or conflation, aiming for a considerably better DEM quality. The geomorphometric methods can also help in the transition from DSM to DTM. The spatial data cleaning principles can be involved in comprehensive generalization tools based on geomorphometry, bearing in mind vertical positional accuracy and different scales. There is also a need to improve a concept using a DEM definition in different scales or resolutions. Nevertheless, does global DEM distribution need a more practical solution in a projected horizontal coordinate system with Cartesian coordinates that optimally preserve their metric properties (areas, distances, and angles), instead of the current geographic coordinates?

This Special Issue is well-timed, because of the recent advances in geomorphometry and spatial data quality approaches. Answers to the research questions can lead to a step forward in the (global) DEM processing, which will further escalate the interoperability and usability.

Dr. Tomaž Podobnikar
Prof. Dr. Juha Oksanen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • global digital elevation model
  • DEM, DSM, and DTM
  • geomorphometry
  • geomorphology
  • spatial analysis
  • data quality
  • uncertainty
  • spatial data cleaning
  • usability
  • spatial data generalization
  • spatial data integration, conflation, and fusion
  • big data processing

Published Papers (9 papers)

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Research

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Article
A Low-Rank Group-Sparse Model for Eliminating Mixed Errors in Data for SRTM1
Remote Sens. 2021, 13(7), 1346; https://doi.org/10.3390/rs13071346 - 01 Apr 2021
Viewed by 662
Abstract
The elimination of mixed errors is a key preprocessing technology for the area of digital elevation model data analysis, which is important for further applying data. We associated group sparsity with the low-rank uniqueness of local transformations of mixing errors to effectively remove [...] Read more.
The elimination of mixed errors is a key preprocessing technology for the area of digital elevation model data analysis, which is important for further applying data. We associated group sparsity with the low-rank uniqueness of local transformations of mixing errors to effectively remove mixing errors in data from Shuttle Radar Topography Mission 1 (SRTM 1) based on the sparseness of low-rank groups. First, the stripe-error structure that appeared globally in multiple directions was able to be better represented locally using group-sparse regularization and the uniqueness of the data in the low-rank direction of the local range and using variational ideas to constrain the gradient direction of the data to avoid redundant elimination. Second, the nonlocal self-similarity of the weighted kernel norm was used to remove random noise. Finally, the proposed model for eliminating mixed errors was solved using an algorithm based on the multiplier method of alternating direction. Experiments using simulated and real data found that the proposed low-rank group-sparse method (LRGS) eliminated mixed errors in both visual and quantitative evaluations better than the most recent processing methods and existing dataset products. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Article
Quality Assessment of TanDEM-X DEMs, SRTM and ASTER GDEM on Selected Chinese Sites
Remote Sens. 2021, 13(7), 1304; https://doi.org/10.3390/rs13071304 - 29 Mar 2021
Viewed by 540
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Article
Evaluating the Vertical Accuracy of DEM Generated from ZiYuan-3 Stereo Images in Understanding the Tectonic Morphology of the Qianhe Basin, China
Remote Sens. 2021, 13(6), 1203; https://doi.org/10.3390/rs13061203 - 22 Mar 2021
Viewed by 561
Abstract
Currently available high-resolution digital elevation model (DEM) is not particularly useful to geologists for understanding the long-term changes in fluvial landforms induced by tectonic uplift, although DEMs that are generated from satellite stereo images such as the ZiYuan-3 (ZY3) satellite include characteristics with [...] Read more.
Currently available high-resolution digital elevation model (DEM) is not particularly useful to geologists for understanding the long-term changes in fluvial landforms induced by tectonic uplift, although DEMs that are generated from satellite stereo images such as the ZiYuan-3 (ZY3) satellite include characteristics with significant coverage and rapid acquisition. Since an ongoing analysis of fluvial systems is lacking, the ZY3 DEM was generated from block adjustment to describe the mountainous area of the Qianhe Basin that have been induced by tectonic uplift. Moreover, we evaluated the overall elevation difference in ZY3 DEM, Shuttle Radar Topography Mission (1″ × 1″) (SRTM1), and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) by using the Ice Cloud and Land Elevation Satellite/Geoscience Laser Altimeter (ICESat/GLAH14) point cloud and a DEM of 1:50,000 scale. The values of the root mean square error (RMSE) of the elevation difference for ZY3 DEM were 9.31 and 9.71 m, respectively, and are in good agreement with SRTM1. The river long profiles and terrace heights were also extracted to compare the differences in channel steepness and the incision rates with SRTM1 and ASTER GDEM. Our results prove that ZY3 DEM would be a good alternative to SRTM1 in achieving the 1:50,000 scale for DEM products in China, while ASTER GDEM is unsuitable for extracting river longitudinal profiles. In addition, the northern and southern river incision rates were estimated using the ages and heights of river terraces, demonstrating a range from 0.12–0.45 to 0.10–0.33 m/kyr, respectively. Collectively, these findings suggest that ZY3 DEM is capable of estimating tectonic geomorphological features and has the potential for analyzing the continuous evolutionary response of a landscape to changes in climate and tectonics. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Article
Identification of Active Gully Erosion Sites in the Loess Plateau of China Using MF-DFA
Remote Sens. 2020, 12(3), 589; https://doi.org/10.3390/rs12030589 - 10 Feb 2020
Cited by 2 | Viewed by 1112
Abstract
Gullies of different scales and types have developed in the Loess Plateau, China. Differences in the amount of gully erosion influence the development, evolution, morphology, and spatial distribution of these gullies. The strengths of headward erosion on the gully shoulder line are used [...] Read more.
Gullies of different scales and types have developed in the Loess Plateau, China. Differences in the amount of gully erosion influence the development, evolution, morphology, and spatial distribution of these gullies. The strengths of headward erosion on the gully shoulder line are used to dictate soil and water conservation measures. In this study, six typical loess landforms in the Loess Plateau were selected as sampling sites: Shenmu, Suide, Ganquan, Yanchuan, Yijun, and Chunhua, which respectively represent loess–aeolian and dune transition zones, loess hills, loess ridge hills, loess ridges, loess long-ridge fragmented tablelands, and loess tablelands. Using 5 m resolution digital elevation model data from the National Basic Geographic Information Database, a small representative watershed was selected from each sampling site to obtain elevation data on the terrain profiles of gully shoulder lines. Multifractal detrended fluctuation analysis (MF-DFA) was used to conduct statistical and comparative analysis of the elevation fluctuation characteristics of these profiles. The results show that MF-DFA is capable of detecting active gully erosion sites. Sites of active gully erosion are concentrated in Shenmu and Suide but more widely distributed in the other five sites. The results provide a scientific basis for small watershed management planning and the design of soil and water conservation measures. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Article
3D Simplification Methods and Large Scale Terrain Tiling
Remote Sens. 2020, 12(3), 437; https://doi.org/10.3390/rs12030437 - 30 Jan 2020
Cited by 3 | Viewed by 1063
Abstract
This paper tackles the problem of generating world-scale multi-resolution triangulated irregular networks optimized for web-based visualization. Starting with a large-scale high-resolution regularly gridded terrain, we create a pyramid of triangulated irregular networks representing distinct levels of detail, where each level of detail is [...] Read more.
This paper tackles the problem of generating world-scale multi-resolution triangulated irregular networks optimized for web-based visualization. Starting with a large-scale high-resolution regularly gridded terrain, we create a pyramid of triangulated irregular networks representing distinct levels of detail, where each level of detail is composed of small tiles of a fixed size. The main contribution of this paper is to redefine three different state-of-the-art 3D simplification methods to efficiently work at the tile level, thus rendering the process highly parallelizable. These modifications focus on the restriction of maintaining the vertices on the border edges of a tile that is coincident with its neighbors, at the same level of detail. We define these restrictions on the three different types of simplification algorithms (greedy insertion, edge-collapse simplification, and point set simplification); each of which imposes different assumptions on the input data. We implement at least one representative method of each type and compare both qualitatively and quantitatively on a large-scale dataset covering the European area at a resolution of 1/16 of an arc minute in the context of the European Marine Observations Data network (EMODnet) Bathymetry project. The results show that, although the simplification method designed for elevation data attains the best results in terms of mean error with respect to the original terrain, the other, more generic state-of-the-art 3D simplification techniques create a comparable error while providing different complexities for the triangle meshes. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Article
High-Resolution and Accurate Topography Reconstruction of Mount Etna from Pleiades Satellite Data
Remote Sens. 2019, 11(24), 2983; https://doi.org/10.3390/rs11242983 - 12 Dec 2019
Cited by 3 | Viewed by 1102
Abstract
The areas characterized by dynamic and rapid morphological changes need accurate topography information with frequent updates, especially if these are populated and involve infrastructures. This is particularly true in active volcanic areas such as Mount (Mt.) Etna, located in the northeastern portion of [...] Read more.
The areas characterized by dynamic and rapid morphological changes need accurate topography information with frequent updates, especially if these are populated and involve infrastructures. This is particularly true in active volcanic areas such as Mount (Mt.) Etna, located in the northeastern portion of Sicily, Italy. The Mt. Etna volcano is periodically characterized by explosive and effusive eruptions and represents a potential hazard for several thousands of local people and hundreds of tourists present on the volcano itself. In this work, a high-resolution, high vertical accuracy digital surface model (DSM) of Mt. Etna was derived from Pleiades satellite data using the National Aeronautics and Space Administration (NASA) Ames Stereo Pipeline (ASP) tool set. We believe that this is the first time that the ASP using Pleiades imagery has been applied to Mt. Etna with sub-meter vertical root mean square error (RMSE) results. The model covers an area of about 400 km2 with a spatial resolution of 2 m and centers on the summit portion of the volcano. The model was validated by using a set of reference ground control points (GCP) obtaining a vertical RMSE of 0.78 m. The described procedure provides an avenue to obtain DSMs at high spatial resolution and elevation accuracy in a relatively short amount of processing time, making the procedure itself suitable to reproduce topographies often indispensable during the emergency management case of volcanic eruptions. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Review

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Review
Digital Elevation Model Quality Assessment Methods: A Critical Review
Remote Sens. 2020, 12(21), 3522; https://doi.org/10.3390/rs12213522 - 27 Oct 2020
Cited by 2 | Viewed by 2823
Abstract
Digital elevation models (DEMs) are widely used in geoscience. The quality of a DEM is a primary requirement for many applications and is affected during the different processing steps, from the collection of elevations to the interpolation implemented for resampling, and it is [...] Read more.
Digital elevation models (DEMs) are widely used in geoscience. The quality of a DEM is a primary requirement for many applications and is affected during the different processing steps, from the collection of elevations to the interpolation implemented for resampling, and it is locally influenced by the landcover and the terrain slope. The quality must meet the user’s requirements, which only make sense if the nominal terrain and the relevant resolution have been explicitly specified. The aim of this article is to review the main quality assessment methods, which may be separated into two approaches, namely, with or without reference data, called external and internal quality assessment, respectively. The errors and artifacts are described. The methods to detect and quantify them are reviewed and discussed. Different product levels are considered, i.e., from point cloud to grid surface model and to derived topographic features, as well as the case of global DEMs. Finally, the issue of DEM quality is considered from the producer and user perspectives. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Other

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Letter
ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD)
Remote Sens. 2020, 12(7), 1156; https://doi.org/10.3390/rs12071156 - 04 Apr 2020
Cited by 20 | Viewed by 1215
Abstract
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 14-channel imaging instrument operating on NASA’s Terra satellite since 1999. ASTER’s visible–near infrared (VNIR) instrument, with three bands and a 15 m Instantaneous field of view (IFOV), is accompanied by an additional [...] Read more.
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 14-channel imaging instrument operating on NASA’s Terra satellite since 1999. ASTER’s visible–near infrared (VNIR) instrument, with three bands and a 15 m Instantaneous field of view (IFOV), is accompanied by an additional band using a second, backward-looking telescope. Collecting along-track stereo pairs, the geometry produces a base-to-height ratio of 0.6. In August 2019, the ASTER Science Team released Version 3 of the global DEM (GDEM) based on stereo correlation of 1.8 million ASTER scenes. The DEM has 1 arc-second latitude and longitude postings (~30 m) and employed cloud masking to avoid cloud-contaminated pixels. Custom software was developed to reduce or eliminate artifacts found in earlier GDEM versions, and to fill holes due to the masking. Each 1×1 degree GDEM tile was manually inspected to verify the completeness of the anomaly removal, which was generally excellent except across some large ice sheets. The GDEM covers all of the Earth’s land surface from 83 degrees north to 83 degrees south latitude. This is a unique, global high spatial resolution digital elevation dataset available to all users at no cost. In addition, a second unique dataset was produced and released. The raster-based ASTER Global Water Body Dataset (ASTWBD) identifies the presence of permanent water bodies, and marks them as ocean, lake, or river. An accompanying DEM file indicates the elevation for each water pixel. To date, over 100 million 1×1 degree GDEM tiles have been distributed. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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Letter
Classification of Karst Fenglin and Fengcong Landform Units Based on Spatial Relations of Terrain Feature Points from DEMs
Remote Sens. 2019, 11(16), 1950; https://doi.org/10.3390/rs11161950 - 20 Aug 2019
Cited by 4 | Viewed by 1100
Abstract
In this paper, a method for extracting Fenglin and Fengcong landform units based on karst topographic feature points is proposed. First, the variable analysis window method is used to extract peaks, nadirs, and saddle points in the karst area based on digital elevation [...] Read more.
In this paper, a method for extracting Fenglin and Fengcong landform units based on karst topographic feature points is proposed. First, the variable analysis window method is used to extract peaks, nadirs, and saddle points in the karst area based on digital elevation model (DEM) data. Thiessen polygons that cover the karst surface area are constructed according to the locations of the peaks and nadirs, and the attributes of the saddles are assigned to corresponding polygons. The polygons are automatically classified via grouping analysis according to the corresponding spatial combinations of peaks, saddles, and nadirs in the Fenglin and Fengcong landform units. Then, a detailed division of the surface morphology of the karst area is achieved by distinguishing various types of Fenglin or Fengcong landform units. Experiments in the Guilin research area show that the proposed method successfully distinguishes the Fenglin and Fengcong terrain areas and extracts Fengcong landform units, individual Fenglin units, and Fenglin chains. The Fengcong area covers approximately two-thirds of the whole area, the individual Fenglin area covers approximately one-fourth, and the Fenglin chain area covers approximately one-tenth. The development of Fenglin has different stages in the Guilin area. This study provides data support for the detailed morphological study of karst terrain, and proposes a new research idea for the division and extraction of karst landform units. Full article
(This article belongs to the Special Issue Advances in Global Digital Elevation Model Processing)
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