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Advancement of Remote Sensing and Photogrammetry in Digital Terrain Modeling and Geomorphometry

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 10123

Special Issue Editor


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Guest Editor
Institute of Mathematical Problems of Biology, Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia
Interests: digital terrain modeling; geomorphometry; surface; topography; unmanned aerial survey; unmanned aerial system; direct georeferencing; structure-from-motion; photogrammetry; three-dimensional modeling; multiscale modeling; DTM; DEM; DSM; error; artifact; accuracy

Special Issue Information

Topography is one of the main factors controlling processes taking place in the near-surface layer of the planet. At the same time, being a result of the interaction of endogenous and exogenous processes of different scales, topography reflects the geological structure of a terrain.

Digital terrain modeling and geomorphometry deals with quantitative modeling and analysis of the topographic surface and relationships between topography and other natural and artificial components of geosystems. Digital terrain analysis and geomorphometric modeling are widely used to solve various multiscale problems of geomorphology, hydrology, soil science, geology, geophysics, geobotany, glaciology, oceanology, climatology, planetology, and other disciplines.

In digital terrain modeling and geomorphometry, the initial data are digital elevation models (DEMs). Currently, DEMs are predominantly produced from remote sensing data. To create medium-resolution DEMs (tens of meters resolution), satellite data are used. Nearly-global models (e.g., SRTM1 DEM, ASTER GDEM, AW3D30 DSM) are currently utilized for producing filtered and edited DEMs with a regional, national, and global coverage. To create high- and very high-resolution DEMs (meter- and centimeter-range resolution), data from unmanned aerial systems (UASs) are used.

To present a current overview of the advancement of remote sensing and photogrammetry in digital terrain modeling and geomorphometry, we invite papers on the following but non-exhaustive list of topics:

  • Methods to produce and edit near-global and regional DEMs using publicly available, satellite-based DEMs (e.g., SRTM1 DEM + ASTER GDEM + AW3D30 DSM);
  • Methods to derive high- and very high-resolution DEMs from UAS-based imagery;
  • Methods to reduce high-frequency noise in UAS-based, high- and very high-resolution DEMs;
  • Methods to remove artifacts from satellite- and UAS-based DEMs;
  • Application of satellite- and UAS-based DEMs to solve multiscale problems of geosciences.

Dr. Igor Florinsky
Guest Editor

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Published Papers (3 papers)

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Research

23 pages, 9717 KiB  
Article
Integrated Laser Scanner Techniques to Produce High-Resolution DTM of Vegetated Territory
by Federica Marotta, Simone Teruggi, Cristiana Achille, Giorgio Paolo Maria Vassena and Francesco Fassi
Remote Sens. 2021, 13(13), 2504; https://doi.org/10.3390/rs13132504 - 26 Jun 2021
Cited by 12 | Viewed by 2455
Abstract
The paper presents the first part of a research project concerning the creation of 3D terrain models useful to understand landslide movements. Thus, it illustrates the creation process of a multi-source high-resolution Digital Terrain Model (DTM) in very dense vegetated areas obtained by [...] Read more.
The paper presents the first part of a research project concerning the creation of 3D terrain models useful to understand landslide movements. Thus, it illustrates the creation process of a multi-source high-resolution Digital Terrain Model (DTM) in very dense vegetated areas obtained by integrating 3D data coming from three sources, starting from long and medium-range Terrestrial Laser Scanner up to a Backpack Indoor Mobile Mapping System. The point clouds are georeferenced by means of RKT GNSS points and automatically filtered using a Cloth Simulation Filter algorithm to separate points belonging to the ground. Those points are interpolated to produce the DTMs which are then mosaicked to obtain a unique multi-resolution DTM that plays a crucial role in the detection and identification of specific geological features otherwise visible. Standard deviation of residuals of the DTM varies from 0.105 m to 0.176 m for Z coordinate, from 0.065 m to 0.300 m for X and from 0.034 m to 0.175 m for Y. The area under investigation belongs to the Municipality of Piuro (SO) and includes both the town and surrounding valley. It was affected by a dramatic landslide in 1618 that destroyed the entire village. Numerous challenges have been faced, caused both by the characteristics of the area and the processed data. The complexity of the case study turns out to be an excellent test bench for the employed technologies, providing the opportunity to precisely identify the needed direction to obtain future promising results. Full article
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22 pages, 37654 KiB  
Article
Mud Volcanism at the Taman Peninsula: Multiscale Analysis of Remote Sensing and Morphometric Data
by Tatyana N. Skrypitsyna, Igor V. Florinsky, Denis E. Beloborodov and Olga V. Gaydalenok
Remote Sens. 2020, 12(22), 3763; https://doi.org/10.3390/rs12223763 - 16 Nov 2020
Cited by 4 | Viewed by 3184
Abstract
Mud volcanism is observed in many tectonically active regions worldwide. One of the typical areas of mud volcanic activity is the Taman Peninsula, Russia. In this article, we examine the possibilities of multiscale analysis of remote sensing and morphometric data of different origins, [...] Read more.
Mud volcanism is observed in many tectonically active regions worldwide. One of the typical areas of mud volcanic activity is the Taman Peninsula, Russia. In this article, we examine the possibilities of multiscale analysis of remote sensing and morphometric data of different origins, years, scales, and resolutions for studying mud volcanic landscapes. The research is exemplified by the central-northern margin of the Taman Peninsula, where mud volcanism has only been little studied. The data set included one arc-second gridded Advanced Land Observing Satellite World three-dimensional (3D) digital surface model (AW3D30 DSM); a Corona historical declassified satellite photography; high-resolution imagery from an unmanned aerial survey (UAS) conducted with a multi-copter drone DJI Phantom 4 Pro, as well as a series of 1-m gridded morphometric models, including 12 curvatures (minimal, maximal, mean, Gaussian, unsphericity, horizontal, vertical, difference, vertical excess, horizontal excess, accumulation, and ring one) derived from UAS-based images. The data analysis allowed us to clarify the conditions of neotectonic development in the central-northern margin of the Taman Peninsula, as well as to specify manifestations of the mud volcanism in this region. In particular, we were able to detect minor and weakly topographically expressed mud volcanic features (probably, inactive gryphons, and salses), which are hidden by long-term farming practice (e.g., ploughed and covered by soil). Full article
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21 pages, 41726 KiB  
Article
A Vector Operation to Extract Second-Order Terrain Derivatives from Digital Elevation Models
by Guanghui Hu, Wen Dai, Sijin Li, Liyang Xiong and Guoan Tang
Remote Sens. 2020, 12(19), 3134; https://doi.org/10.3390/rs12193134 - 24 Sep 2020
Cited by 13 | Viewed by 3642
Abstract
Terrain derivatives exhibit surface morphology in various aspects. However, existing spatial change calculation methods for terrain derivatives are based on a mathematical scalar operating system, which may disregard the directional property of the original data to a certain extent. This situation is particularly [...] Read more.
Terrain derivatives exhibit surface morphology in various aspects. However, existing spatial change calculation methods for terrain derivatives are based on a mathematical scalar operating system, which may disregard the directional property of the original data to a certain extent. This situation is particularly true in second-order terrain derivatives, in which original data can be terrain derivatives with clear directional properties, such as slope or aspect. Thus, this study proposes a mathematical vector operation method for the calculation of second-order terrain derivatives. Given the examples of the first-order terrain derivatives of slope and aspect, their second-order terrain derivatives are calculated using the proposed vector method. Directional properties are considered and vectorized using the following steps: rotation-type judgment, standardization of initial direction, and vector representation. The proposed vector method is applied to one mathematical Gaussian surface and three different ground landform areas using digital elevation models (DEMs) with 5 and 1 m resolutions. Comparison analysis results between the vector and scalar methods show that the former achieves more reasonable and accurate second-order terrain derivatives than the latter. Moreover, the vector method avoids overexpression or even exaggeration errors. This vector operation concept and its expanded methods can be applied in calculating other terrain derivatives in geomorphometry. Full article
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