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: closed (31 March 2020).

Special Issue Editors

Dr. Tomaž Podobnikar
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
Prof. Dr. Juha Oksanen
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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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 (5 papers)

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Open AccessArticle
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
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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Open AccessArticle
3D Simplification Methods and Large Scale Terrain Tiling
Remote Sens. 2020, 12(3), 437; https://doi.org/10.3390/rs12030437 - 30 Jan 2020
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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Open AccessArticle
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
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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Open AccessLetter
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 (registering DOI) - 04 Apr 2020
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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Open AccessLetter
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 1
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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