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Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue, “Advances in Synthetic Aperture Radar: Calibration, Analysis, and Application”, a new one has been opened for submissions.

Over the last decade, the study of human–environment relationships has demonstrated further importance, as we need to ask how to utilize and protect the natural world, how to build and optimize infrastructure, and how to prepare and respond to disasters in a better way. In order to find the answers, we usually need to collect global, continuous, and/or precise environmental information using remote sensing methods. Synthetic aperture radar (SAR) is known for its imaging potential in situations where darkness, clouds, or smoke would obscure the view of optical sensors, and so it is highly useful for environmental observing. Nowadays, SAR scientific and technical innovations in calibration, information extraction, new imaging techniques, and algorithm adjusting for various specific applications are required.

This Special Issue aims to publish studies covering almost all topics related to SAR. Hence, studies are welcome that focus on the basic theory, calibration, data processing, image interpretation (such as with decomposition algorithms), and various applications of SAR. Articles may address, but are not limited, to the following topics:

Calibration of SAR data;
SAR applications;
Present and future SAR systems and missions;
Electromagnetic modeling;
InSAR and high-resolution SAR;
POL and POLInSAR;
Bistatic SAR;
SAR/GMTI/STAP and change detection;
Image filtering, correction and enhancement;
SAR/ISAR signal processing;
Advanced and innovative SAR concepts and modes;
Artificial intelligence algorithms and their applications in SAR.

Dr. Fang Shang
Dr. Lamei Zhang
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.

Related Special Issue

Published Papers (1 paper)

Research

16 pages, 6420 KiB

Open AccessArticle

Near Real-Time Monitoring of Large Gradient Nonlinear Subsidence in Mining Areas: A Hybrid SBAS-InSAR Method Integrating Robust Sequential Adjustment and Deep Learning

by Yuanjian Wang, Ximin Cui, Yuhang Che, Yuling Zhao, Peixian Li, Xinliang Kang and Yue Jiang

Remote Sens. 2024, 16(10), 1664; https://doi.org/10.3390/rs16101664 - 8 May 2024

Viewed by 526

Abstract

With the increasing availability of satellite monitoring data, the demand for storage and computational resources for updating the results of monitoring the surface subsidence in a mining area continues to rise. Sequential adjustment (SA) models are considered effective for rapidly updating time series interferometry synthetic aperture radar (TS-InSAR) measurements. However, the accuracy of surface subsidence values estimated through traditional sequential adjustment is highly sensitive to abnormal observations or prior information on anomalies. Moreover, the surface subsidence associated with mining exhibits nonlinear and large gradient characteristics, making general InSAR methods challenging for obtaining reliable monitoring results. In this study, we employ the phase unwrapping network (PUNet) to obtain unwrapped values of differential interferograms. To mitigate the impact of abnormal errors in the near real-time small baseline subset InSAR (SBAS-InSAR) sequential updating process in mining areas, a robust sequential adjustment method based on M-estimation is proposed to estimate the temporal deformation parameters by using the equivalent weight model. Using a coal backfilling mining face in Shanxi, China, as the study area and the Sentinel-1 SAR dataset, we comprehensively evaluate the performance of unwrapping methods and subsidence time series estimation techniques and evaluate the effect of filling mining on surface subsidence control. The results are validated using leveling measurements within the study area. The relative error of the proposed method is less than 5%, which can meet the requirements of monitoring the surface subsidence in mining areas. The method proposed in this study not only enhances computational efficiency but also addresses the issue of underestimation encountered by InSAR methods in mining area applications. Furthermore, it also mitigates unwrapping phase anomalies on the monitoring results. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar: Calibration, Analysis and Application II)

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