scholarly journals Retrieval of digital elevation models from Sentinel-1 radar data – open applications, techniques, and limitations

2021 ◽  
Vol 13 (1) ◽  
pp. 532-569
Author(s):  
Andreas Braun
Keyword(s):  
Digital Elevation Models ◽  
Radar Data ◽  
Error Sources ◽  
New Era ◽  
Differential Interferometry ◽  
Digital Elevation ◽  
Radar Imagery ◽  
Solid Foundation ◽  
The Impact ◽  
Spaceborne Radar

Abstract With the launch of Sentinel-1 in 2014, a new era of openly accessible spaceborne radar imagery was begun, and its potential has been demonstrated throughout all fields of applications. However, while interferometric approaches to detect surface deformations are continuously being published, only a few studies address the derivation of digital elevation models (DEMs) from Sentinel-1 data. This is mainly because of the narrow orbital tube, which was primarily designed for subsidence measurements using differential interferometry. Nonetheless, the technical conditions are provided for successful applications involving DEM generation. These are outlined in the first part of this article with a focus on potential error sources and the impact of the most important constraints, namely, temporal and perpendicular baselines. The second part evaluates 21 studies on this topic, their aims, and how they dealt with error sources and the necessity of validation. These studies are then discussed based on the main challenges and potentials including how these can be tackled in the future to lay a solid foundation for scientific discourse.

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 Investigating the Impact of Digital Elevation Models on Sentinel-1 Backscatter and Coherence Observations

2020 ◽  
Vol 12 (18) ◽  
pp. 3016
Author(s):  
Ignacio Borlaf-Mena ◽  
Maurizio Santoro ◽  
Ludovic Villard ◽  
Ovidiu Badea ◽  
Mihai Andrei Tanase
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Elevation Models ◽  
Shuttle Radar Topography Mission ◽  
Synthetic Aperture ◽  
Mountainous Regions ◽  
Aerial Laser Scanning ◽  
Digital Elevation ◽  
The Difference ◽  
The Impact

Spaceborne remote sensing can track ecosystems changes thanks to continuous and systematic coverage at short revisit intervals. Active remote sensing from synthetic aperture radar (SAR) sensors allows day and night imaging as they are not affected by cloud cover and solar illumination and can capture unique information about its targets. However, SAR observations are affected by the coupled effect of viewing geometry and terrain topography. The study aims to assess the impact of global digital elevation models (DEMs) on the normalization of Sentinel-1 backscattered intensity and interferometric coherence. For each DEM, we analyzed the difference between orbit tracks, the difference with results obtained with a high-resolution local DEM, and the impact on land cover classification. Tests were carried out at two sites located in mountainous regions in Romania and Spain using the SRTM (Shuttle Radar Topography Mission, 30 m), AW3D (ALOS (Advanced Land Observation Satellite) World 3D, 30 m), TanDEM-X (12.5, 30, 90 m), and Spain national ALS (aerial laser scanning) based DEM (5 m resolution). The TanDEM-X DEM was the global DEM most suitable for topographic normalization, since it provided the smallest differences between orbital tracks, up to 3.5 dB smaller than with other DEMs for peak landform, and 1.4–1.9 dB for pit and valley landforms.

Assessing the Impact of Uncertainties of Digital Elevation Models on Hydro-Geomorphological Analysis Using Gaussian White Noise

2020 ◽  
Author(s):  
Lukas Graf ◽  
Mariano Moreno-de-las-Heras ◽  
Joan Estrany
Keyword(s):  
White Noise ◽  
Imperfect Information ◽  
Digital Elevation Models ◽  
Gaussian White Noise ◽  
Terrain Analysis ◽  
Stream Network ◽  
Digital Terrain ◽  
Digital Elevation ◽  
The Impact ◽  
Geomorphological Analysis

<p><span>Digital elevation models (DEM) are mathematical representations of the Earth's bare surface in computer-readable format. The underlying measurements are often obtained by remote sensing and photogrammetry methods and processed into continuous raster data. Each of these data sources, however, provides imperfect information, and further processing steps often increase the degree of imperfection. Consequently, the process of DEM generation cumulates in uncertainty, which affects subsequent hydro- and geomorphological analyses and modelling (e.g., stream network delineation, flowpath distribution, erosion modelling).</span></p> <p><span>In many DEM-based studies, however, the aspect of uncertainty related to the DEM data source has been neglected. Therefore, we propose a new approach for quantifying the effects of DEM uncertainty on hydro-geomorphological modelling based on Gaussian white noise, a concept widely used in signal processing to map noise in signals and extract the actual message context. The basic idea is to add noise to the original DEM values by means of a Gaussian distribution whose parameters are determined from the mean value of the elevation values in a moving window and the device-specific properties (precision and accuracy).</span></p> <p><span>We postulate that such an approach can be used to determine uncertainties and their effect on subsequent analysis steps of hydro-geomorphological modelling. It is conceivable to create DEM ensembles depending on known parameters such as the accuracy and precision of the measuring instrument, as is used operationally in weather forecasting. Using such ensembles, probability ranges for terrain and catchment hydro-geomorphological properties can be determined and uncertainty ranges can be specified. Thus, the currently mostly deterministic approach of digital terrain modelling will be replaced by a more probabilistic understanding. Overall, our approach will help decision-makers and scientists to better assess the results of digital terrain analysis. Furthermore, it will also facilitate determining whether a result of DEM-based hydro-geomorphological analysis is sufficiently certain to answer specific research questions.</span></p>

scholarly journals Assessing the impact of sea level rise on port operability using LiDAR-derived digital elevation models

2019 ◽  
Vol 232 ◽  
pp. 111318 ◽  
Author(s):  
Vicente Gracia ◽  
Joan Pau Sierra ◽  
Marta Gómez ◽  
Mónica Pedrol ◽  
Sara Sampé ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Digital Elevation Models ◽  
Digital Elevation ◽  
The Impact

scholarly journals Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review

2019 ◽  
Vol 8 (12) ◽  
pp. 545 ◽  
Author(s):  
Nayyer Saleem ◽  
Md. Enamul Huq ◽  
Nana Yaw Danquah Twumasi ◽  
Akib Javed ◽  
Asif Sajjad
Keyword(s):  
Risk Assessment ◽  
Landslide Susceptibility ◽  
3D Visualization ◽  
Digital Elevation Models ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Landslide Risk ◽  
Conditioning Factors ◽  
Digital Elevation ◽  
The Impact

Digital elevation models (DEMs) are considered an imperative tool for many 3D visualization applications; however, for applications related to topography, they are exploited mostly as a basic source of information. In the study of landslide susceptibility mapping, parameters or landslide conditioning factors are deduced from the information related to DEMs, especially elevation. In this paper conditioning factors related with topography are analyzed and the impact of resolution and accuracy of DEMs on these factors is discussed. Previously conducted research on landslide susceptibility mapping using these factors or parameters through exploiting different methods or models in the last two decades is reviewed, and modern trends in this field are presented in a tabulated form. Two factors or parameters are proposed for inclusion in landslide inventory list as a conditioning factor and a risk assessment parameter for future studies.

scholarly journals How Well Can Spaceborne Digital Elevation Models Represent a Man-Made Structure: A Runway Case Study

2019 ◽  
Author(s):  
Kazimierz Becek ◽  
Volkan Akgül ◽  
Samed Inyurt ◽  
Çetin Mekik ◽  
Patrycja Pochwatka
Keyword(s):  
Flat Surface ◽  
Digital Elevation Models ◽  
High Accuracy ◽  
Surface Material ◽  
Reference Dataset ◽  
Error Sources ◽  
Ground Survey ◽  
Digital Elevation ◽  
Selection Of

In this case study, an active runway of a civilian airport in Zonguldak, Turkey, is used to assess the suitability of spaceborne digital elevation models (DEMs) to model an anthropogenic structure. The tested DEMs include the ASTER, the AW3D30 m, the SRTM-1”, the SRTM-3”, the SRTM-X, the TanDEM-3”, and the WorldDEMTM. A photogrammetric high accuracy DEM was also available for the tests. As a reference dataset, a line leveling survey of the runway using a Leica Sprinter 150/150M instrument was performed. The selection of a runway as a testbed for this type of investigation is justified by its unique characteristics, including its flat surface, homogenous surface material, and availability for a ground survey. These characteristics are significant because DEMs over similar structures are free from environment- and target-induced error sources. The most accurate DEM is the WorldDEMTM followed by the SRTM-3” and TanDEM-3”, with vertical errors (LE90) equal to 1.291 m, 1.542 m, and 1.56 m, respectively. This investigation uses a method for identifying the vertical errors in DEMs that is known as the runway method.

Advances in using radar to observe vegetation water dynamics

2020 ◽  
Author(s):  
Susan Steele-Dunne ◽  
Paul Vermunt ◽  
Saeed Khabbazan ◽  
Ashwini Petchiappan ◽  
Jasmeet Judge ◽  
...  
Keyword(s):  
Water Content ◽  
Temporal Dynamics ◽  
Radar Data ◽  
Global Scale ◽  
Water Dynamics ◽  
Radar Observations ◽  
Vegetation Water ◽  
Meaningful Relationships ◽  
The Impact ◽  
Spaceborne Radar

<p>Vegetation acts as an interface between the earth's surface and the atmosphere, modulating exchanges of water, carbon and energy and responding to environmental stressors. Improved understanding of water transport through the soil-vegetation-atmosphere continuum is essential to understand the role of vegetation at a catchment and a global scale. The sensitivity of radar remote sensing observations to the water content of soil and vegetation makes it well-suited to monitoring spatio-temporal dynamics of processes in the soil-vegetation-atmosphere continuum.</p><p>Here, we present the latest results from studies using ground-based and spaceborne radar demonstrating the potential of radar to monitor vegetation water dynamics at scales from meters to tens of kilometers. Field data will be used to demonstrate the sensitivity of radar observations to surface and internal vegetation water content. These results illustrate the potential value of radar for monitoring rapid plant water dynamics, and the impact of water-limited conditions on land-atmosphere exchanges. Satellite data will be used to illustrate the degree to which current spaceborne radar systems can already be used to monitor these processes and the limitations posed by revisit time and resolution.</p><p>We will conclude with an outline of future opportunities and challenges. The next generation of spaceborne radar sensors offers  unprecedented monitoring capability. To avail of this opportunity, we need improved alignment between the treatment of vegetation in hydrological and radiative transfer models. This is essential to ensure meaningful relationships between new radar data products and hydrological states of interest, and to facilitate the assimilation of radar observations to constrain vegetation processes in hydrological models.</p>

scholarly journals Surface and bed topography of Trapridge Glacier, Yukon Territory, Canada: digital elevation models and derived hydraulic geometry

1999 ◽  
Vol 45 (149) ◽  
pp. 165-174 ◽  
Author(s):  
Gwenn E. Flowers ◽  
Garry K. C. Clarke
Keyword(s):  
Digital Elevation Models ◽  
Water Pressure ◽  
Geometric Analysis ◽  
Radar Data ◽  
Yukon Territory ◽  
Bed Topography ◽  
Digital Elevation ◽  
Basin Scale ◽  
Hydrological System ◽  
Trapridge Glacier

AbstractMeasurements of ice thickness and surface elevation are prerequisite to many glaciological investigations. A variety of techniques has been developed for interpretation of these data, including means of constructing regularly gridded digital elevation models (DEMs) for use in numerical studies. Here we present a simple yet statistically sound method for processing ice-penetrating radar data and describe a technique for interpolating these data onto a regular grid. DEMs generated for Trapridge Glacier, Yukon Territory, Canada, are used to derive geometric quantities that give preliminary insights into the underlying basin-scale hydrological system. This simple geometric analysis suggests that at low water pressures a dendritic drainage network exists that evolves into a uniaxial morphology as water pressure approaches flotation. These predictions are compared to hydraulic connection probabilities based on borehole drilling.

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