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SAR Remote Sensing of Arid Regions

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 (1 August 2021) | Viewed by 8752

Special Issue Editors

Department of Geography, RWTH Aachen University, Aachen, Germany
Interests: geomorphology; palaeoclimatology; pysical geography; remote sensing; land surface dynamics
Institute of Geography and Geology, University of Würzburg, Wurzburg, Germany
Interests: geomorphology; physical geography; archaeology; SAR image analysis; environmental sciences; land surface dynamics

Special Issue Information

Dear Colleagues,

Thanks to the Sentinel-1 mission, high-resolution synthetic aperture radar (SAR) remote sensing data with high temporal and spatial resolution have become freely available for almost all regions of the earth, providing complementary information to optical remote sensing systems. This extensive data archive and the planned continuation of the mission open up new perspectives for the recognition, observation, and analysis of land surface dynamics, especially in arid landscapes, and offer a high potential for physiogeographic research.

For this Special Issue, contributions are sought which demonstrate applications of radar remote sensing to problems in physical geography and geomorphology, especially for hyper-arid, arid, or semi-arid regions. We are looking for contributions from all fields of physical–geographical research using data from radar remote sensing systems (e.g., Sentinel-1, TerraSAR-X, Radarsat-2). The focus can be, but is not limited to: the fusion of optical and radar data in mapping and classification of the land surface, the derivation of motion rates and surface changes by feature tracking and/or interferometry, coherence and/or amplitude change detection, and the identification/quantification of morphological dynamics by time series analysis.

Dr. Georg Stauch
Dr. Tobias Ullmann
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 submissions that pass pre-check are 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 2700 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

  • Synthetic aperture radar
  • Geomorphology
  • Land surface
  • Dynamics
  • Change detection
  • Physical geography

Published Papers (2 papers)

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Research

22 pages, 6650 KiB  
Article
Sand Dune Dynamics Exploiting a Fully Automatic Method Using Satellite SAR Data
by José Manuel Delgado Blasco, Marco Chini, Gert Verstraeten and Ramon F. Hanssen
Remote Sens. 2020, 12(23), 3993; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12233993 - 06 Dec 2020
Cited by 10 | Viewed by 4335
Abstract
This work presents an automatic procedure to quantify dune dynamics on isolated barchan dunes exploiting Synthetic Aperture RADAR satellite data. We use C-band datasets, allowing the multi-temporal analysis of dune dynamics in two study areas, one located between the Western Sahara and Mauritania [...] Read more.
This work presents an automatic procedure to quantify dune dynamics on isolated barchan dunes exploiting Synthetic Aperture RADAR satellite data. We use C-band datasets, allowing the multi-temporal analysis of dune dynamics in two study areas, one located between the Western Sahara and Mauritania and the second one located in the South Rayan dune field in Egypt. Our method uses an adaptive parametric thresholding algorithm and common geospatial operations. A quantitative dune dynamics analysis is also performed. We have measured dune migration rates of 2–6 m/year in the NNW-SSE direction and 11–20 m/year NNE-SSW for the South Rayan and West-Sahara dune fields, respectively. To validate our results, we have manually tracked several dunes per study area using Google Earth imagery. Results from both automatic and manual approaches are consistent. Finally, we discuss the advantages and limitations of the approach presented. Full article
(This article belongs to the Special Issue SAR Remote Sensing of Arid Regions)
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26 pages, 12120 KiB  
Article
Surface Roughness Estimation in the Orog Nuur Basin (Southern Mongolia) Using Sentinel-1 SAR Time Series and Ground-Based Photogrammetry
by Tobias Ullmann and Georg Stauch
Remote Sens. 2020, 12(19), 3200; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12193200 - 30 Sep 2020
Cited by 12 | Viewed by 3832
Abstract
This study demonstrates an application-oriented approach to estimate area-wide surface roughness from Sentinel-1 time series in the semi-arid environment of the Orog Nuur Basin (southern Mongolia) to support recent geomorphological mapping efforts. The relation of selected mono- and multi-temporal SAR features and roughness [...] Read more.
This study demonstrates an application-oriented approach to estimate area-wide surface roughness from Sentinel-1 time series in the semi-arid environment of the Orog Nuur Basin (southern Mongolia) to support recent geomorphological mapping efforts. The relation of selected mono- and multi-temporal SAR features and roughness is investigated by using an empirical multi-model approach and selected 1D and 2D surface roughness indices. These indices were obtained from 48 high-resolution ground-based photogrammetric digital elevation models, which were acquired during a single field campaign. The analysis is backed by a time series analysis, comparing Sentinel-1 features to temporal-corresponding observations and reanalysis datasets on soil moisture conditions, land surface temperature, occurrence of precipitation events, and presence and development of vegetation. Results show that Sentinel-1 features are hardly sensitive to the changing surface conditions over none to sparsely vegetated land, indicating very dry conditions throughout the year. Consequently, surface roughness is the dominating factor altering SAR intensity. The best correlation is found for the combined surface roughness index Z-Value (ratio between the root mean square height and the correlation length) and the mean summer VH intensity with an r2 coefficient of 0.83 and an Root-Mean-Square Error of 0.032. Full article
(This article belongs to the Special Issue SAR Remote Sensing of Arid Regions)
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