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Remote Sensing
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Land and Ocean Disaster Monitoring Based on Navigation Satellite Systems
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Land and Ocean Disaster Monitoring Based on Navigation Satellite Systems

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

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 7091

Special Issue Editors

Prof. Kegen Yu

E-Mail Website
Guest Editor
School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221000, China
Interests: GNSS reflectometry; ground-based and satellite-based positioning; remote sensing; signal processing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Weimin Huang

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Memorial University, St. John’s, NL A1B 3X5, Canada
Interests: mapping of oceanic surface parameters via high-frequency ground wave radar; X-band marine radar and global navigation satellite systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, there are over 100 operational navigation satellites in space, which belong to the four global navigation satellite systems (China’s BDS, the EU’s Galileo, Russia’s GLONASS, and the USA’s GPS), India’s IRNSS, and Japan’s QZSS. Although these satellites were built and are managed by different countries and are located on three different types of orbits (MEO, GEO, and IGSO), they all transmit L-band radio signals with frequencies mainly between 1.2 and 1.6 GHz. These signals are precious resources which are not only used for positioning, navigation, and timing, but also for remote sensing. As the two remote sensing technologies derived from navigation satellite systems, GNSS radio occultation (GNSS-RO) and GNSS reflectometry (GNSS-R) have been extensively investigated for sensing atmosphere and earth surface over the past several decades. The precise position measurements provided by ground-based GNSS receivers have also been utilized for various monitoring applications.

This Special Issue focuses on the use of signals and data recorded by GNSS receivers which can be ground-based, carried by aircrafts, or by satellites for monitoring and warning of land and ocean disasters. There is a range of land and ocean disasters, including earthquakes, volcanoes, landslides, flooding, damaging wave, tsunamis, storm surge, hurricanes/typhoons, and ocean pollution. These disasters, some of which might be associated with human activities, have caused tremendous economic damage and many life losses, as well as great environmental and ecological problems. Although many monitoring and warning systems have been established worldwide, it is important to also make use of navigation satellite systems to achieve efficient and cost-effective solutions to monitor disasters. In fact, a number of systems which use GNSS signals have already been developed for disaster monitoring, including CYGNSS, Bufeng-1, and FY3E. This Special Issue seeks the latest theories and methodologies and software and hardware designs based on navigation satellite systems for disaster monitoring and warning. Topics of interest in this Special Issue include but are not limited to:

  • Land disaster monitoring
  • Cryosphere disaster monitoring
  • Ocean disaster monitoring
  • Disaster warning
  • Post-disaster services
  • Software and hardware design for disaster monitoring
  • LEO satellite missions for disaster monitoring
  • Experimental campaigns for disaster monitoring

Prof. Kegen Yu
Prof. Weimin Huang
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

  • Land disaster monitoring
  • Cryosphere disaster monitoring
  • Ocean disaster monitoring
  • Disaster warning
  • Post-disaster services
  • Software and hardware design for disaster monitoring
  • LEO satellite missions for disaster monitoring
  • Experimental campaigns for disaster monitoring

Published Papers (3 papers)

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Research

18 pages, 14322 KiB  
Article
A Novel Index for Daily Flood Inundation Retrieval from CYGNSS Measurements
by Ting Yang, Zhigang Sun and Lulu Jiang
Remote Sens. 2023, 15(2), 524; https://doi.org/10.3390/rs15020524 - 16 Jan 2023
Cited by 1 | Viewed by 2726
Abstract
Since flood inundation hampers human life and the economy, flood inundation retrieval with high temporal resolution and accuracy is essential for the projection of the environmental impact. In this study, a novel cyclone global navigation satellite system (CYGNSS)-based index, named the annual threshold [...] Read more.
Since flood inundation hampers human life and the economy, flood inundation retrieval with high temporal resolution and accuracy is essential for the projection of the environmental impact. In this study, a novel cyclone global navigation satellite system (CYGNSS)-based index, named the annual threshold flood inundation index (ATFII) for flood inundation retrieval, is proposed, and the grades of flood inundation are quantified. First, the CYGNSS surface reflectivity with land surface properties (i.e., vegetation and surface roughness) calibration is derived based on the zeroth-order radiative transfer model. Then, an index named ATFII is proposed to achieve inundation retrieval, and the inundation grades are classified. The results are validated with the Visible Infrared Imaging Radiometer Suite (VIIRS) flood product and GPM precipitation data. The validation results between ATFII and GPM precipitation indicate that the ATFII enables flood inundation retrieval at rapid timescales and quantifies the inundation variation grades. Likewise, for monthly results, the R value between the VIIRS flood product and ATFII varies from 0.51 to 0.64, with an acceptable significance level (p < 0.05). The study makes contributions in two aspects: (1) it provides an index-based method for mapping daily flood inundation on a large scale, with the advantages of fast speed and convenience, and (2) it provides a new way to derive inundation grade variations, which can help in studying the behavior of inundation in response to environmental impacts directly. Full article
(This article belongs to the Special Issue Land and Ocean Disaster Monitoring Based on Navigation Satellite Systems)
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17 pages, 5316 KiB  
Article
Estimation of Ground Subsidence Deformation Induced by Underground Coal Mining with GNSS-IR
by Huaizhi Bo, Yunwei Li, Xianfeng Tan, Zhoubin Dong, Guodong Zheng, Qi Wang and Kegen Yu
Remote Sens. 2023, 15(1), 96; https://doi.org/10.3390/rs15010096 - 24 Dec 2022
Cited by 2 | Viewed by 1557
Abstract
In this paper, GNSS interferometric reflectometry (GNSS-IR) is firstly proposed to estimate ground surface subsidence caused by underground coal mining. Ground subsidence on the main direction of a coal seam is described by using the probability integral model (PIM) with unknown parameters. Based [...] Read more.
In this paper, GNSS interferometric reflectometry (GNSS-IR) is firstly proposed to estimate ground surface subsidence caused by underground coal mining. Ground subsidence on the main direction of a coal seam is described by using the probability integral model (PIM) with unknown parameters. Based on the laws of reflection in geometric optics, model of GNSS signal-to-noise (SNR) observation for the tilt surface, which results from differential subsidence of ground points, is derived. Semi-cycle SNR observations fitting method is used to determine the phase of the SNR series. Phase variation of the SNR series is used to calculate reflector height of ground specular reflection point. Based on the reflector height and ground tilt angle, an iterative algorithm is proposed to determine coefficients of PIM, and thus subsidence of the ground reflection point. By using the low-cost navigational GNSS receiver and antenna, an experimental campaign was conducted to validate the proposed method. The results show that, when the maximum subsidence is 3076 mm, the maximum relative error of the proposed method-based subsidence estimation is 5.5%. This study also suggests that, based on the proposed method, the navigational GNSS instrument can be treated as a new type of sensor for continuously measuring ground subsidence deformation in a cost-effective way. Full article
(This article belongs to the Special Issue Land and Ocean Disaster Monitoring Based on Navigation Satellite Systems)
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Graphical abstract

22 pages, 42728 KiB  
Article
Estimation of Swell Height Using Spaceborne GNSS-R Data from Eight CYGNSS Satellites
by Jinwei Bu, Kegen Yu, Hyuk Park, Weimin Huang, Shuai Han, Qingyun Yan, Nijia Qian and Yiruo Lin
Remote Sens. 2022, 14(18), 4634; https://doi.org/10.3390/rs14184634 - 16 Sep 2022
Cited by 8 | Viewed by 1976
Abstract
Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) technology has opened a new window for ocean remote sensing because of its unique advantages, including short revisit period, low observation cost, and high spatial-temporal resolution. In this article, we investigated the potential of estimating swell height [...] Read more.
Global Navigation Satellite System (GNSS)-Reflectometry (GNSS-R) technology has opened a new window for ocean remote sensing because of its unique advantages, including short revisit period, low observation cost, and high spatial-temporal resolution. In this article, we investigated the potential of estimating swell height from delay-Doppler maps (DDMs) data generated by spaceborne GNSS-R. Three observables extracted from the DDM are introduced for swell height estimation, including delay-Doppler map average (DDMA), the leading edge slope (LES) of the integrated delay waveform (IDW), and trailing edge slope (TES) of the IDW. We propose one modeling scheme for each observable. To improve the swell height estimation performance of a single observable-based method, we present a data fusion approach based on particle swarm optimization (PSO). Furthermore, a simulated annealing aided PSO (SA-PSO) algorithm is proposed to handle the problem of local optimal solution for the PSO algorithm. Extensive testing has been performed and the results show that the swell height estimated by the proposed methods is highly consistent with reference data, i.e., the ERA5 swell height. The correlation coefficient (CC) is 0.86 and the root mean square error (RMSE) is 0.56 m. Particularly, the SA-PSO method achieved the best performance, with RMSE, CC, and mean absolute percentage error (MAPE) being 0.39 m, 0.92, and 18.98%, respectively. Compared with the DDMA, LES, TES, and PSO methods, the RMSE of the SA-PSO method is improved by 23.53%, 26.42%, 30.36%, and 7.14%, respectively. Full article
(This article belongs to the Special Issue Land and Ocean Disaster Monitoring Based on Navigation Satellite Systems)
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