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Remote Sensing
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RADARSAT Constellation Mission (RCM)
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RADARSAT Constellation Mission (RCM)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 12746

Special Issue Editors

Dr. Masoud Mahdianpari

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St. John’s, NL A1C 5S7, Canada
Interests: remote sensing; geospatial data; machine learning; geo big data; wetland; GHG monitoring
Special Issues, Collections and Topics in MDPI journals
Dr. Fariba Mohammadimanesh

E-Mail Website
Guest Editor
Research Scientist, C-CORE and Memorial University of Newfoundland, St. John’s, NL, Canada
Interests: remote sensing; PolSAR data analysis; InSAR for geo-hazard monitoring; deep learning; geo big data
Special Issues, Collections and Topics in MDPI journals
Dr. Brian Brisco

E-Mail Website
Guest Editor
Sr. Scientist, Canada Center for Mapping and Earth Observation, Ottawa, ON, Canada
Interests: wetlands; SAR; surface water mapping
Special Issues, Collections and Topics in MDPI journals
Dr. Bahram Salehi

E-Mail Website
Guest Editor
College of Environmental Science and Forestry (SUNY-ESF), State University of New York, Syracuse, NY 13210, USA
Interests: remote sensing of environment (wetland, permafrost, forest, oil spill, land cover, harmful algal bloom, etc.); SAR (PolSAR and InSAR) remote sensing; photogrammetry and image processing of UAVs; machine learning and image processing; nanosatellite data processing
Special Issues, Collections and Topics in MDPI journals
Dr. Saeid Homayouni

E-Mail Website
Guest Editor
Institut National de la Recherche Scientifique (INRS), Centre Eau Terre Environnement, 490, rue de la Couronne, Québec, QC G1K 9A9, Canada
Interests: analysis of optical; hyperspectral and radar Earth observations through artificial intelligence and machine-learning approaches for urban and agro-environmental applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

On June 12, 2019, Canada launched the next generation of C-band SAR satellites, the RADARSAT Constellation Mission (RCM), with the capability to collect data in various polarization configurations, including compact polarimetry (CP) mode. The main purpose of the mission is to ensure data continuity for RADARSAT users and improve the operational capability of SAR data by leveraging a more advanced spaceborne mission. In particular, RCM comprises three identical small C-band satellites gaining a greater coverage over a much shorter revisit time (subweekly) compared to its predecessors, RADARSAT-1 and -2. This state-of-the-art satellite mission provides daily coverage of Canada’s vast landmass, oceans, and coasts, while covering the high Arctic up to four times a day. It also has daily access to most of the world’s surface (i.e., over 90%).

Thanks to its multipolarization capability, large swath coverage, and high temporal resolution, RCM opens unprecedented opportunities for several remote sensing applications. For example, RCM will provide ideal SAR data for several ocean applications, such as sea ice monitoring, ship detection, and oil spill response. Furthermore, its enhanced temporal resolution makes RCM an ideal source of collecting SAR data for applications demanding frequent SAR observations, such as agriculture, coherent change detection, and wetland water level monitoring using interferometric SAR (InSAR). It is expected data collected from this new generation of SAR satellites will be available for both scientific and user communities shortly.

This Special Issue on “RADARSAT Constellation Mission” focuses on different applications and algorithm developments of data collected by RCM. We would like to invite articles on remote sensing applications using this state-of-the-art SAR data and in combination with other data and techniques. Submissions are encouraged to cover a broad range of topics, which may include, without being limited to, the following subjects:

  • Ocean applications (e.g., sea ice monitoring, wind retrieval, iceberg and ship detection);
  • Urban mapping;
  • Climate change monitoring;
  • Deformation measurements;
  • Wetland mapping and monitoring;
  • Biomass estimation;
  • Glacier- and permafrost-related hazards;
  • Surface soil moisture;
  • Coastal changes;
  • Agricultural applications;
  • Large-scale mapping;
  • Oil spill detection;
  • Land cover classification;
  • Ecosystem monitoring;
  • Disaster management (mitigation, warning, response, and recovery);
  • Data calibration.

The submission of overview papers on simulated or real RCM data should be coordinated with the editors to avoid overlapping and conflicts.

Dr. Masoud Mahdianpari
Dr. Fariba Mohammadimanesh
Dr. Brian Brisco
Dr. Bahram Salehi
Dr. Saeid Homayouni
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 (SAR)
  • Polarimetric SAR
  • RADARSAT Constellation Mission (RCM)
  • Compact Polarimetry
  • Rremote Sensing
  • Maritime Surveillance
  • Ecosystem Monitoring
  • Agriculture
  • Climate Change Monitoring
  • Machine Learning
  • Deep Learning

Published Papers (4 papers)

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Research

19 pages, 7823 KiB  
Article
The RADARSAT Constellation Mission Core Applications: First Results
by Mohammed Dabboor, Ian Olthof, Masoud Mahdianpari, Fariba Mohammadimanesh, Mohammed Shokr, Brian Brisco and Saeid Homayouni
Remote Sens. 2022, 14(2), 301; https://doi.org/10.3390/rs14020301 - 10 Jan 2022
Cited by 9 | Viewed by 3695
Abstract
The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture radar (SAR) meets the expectations of intended users. In this [...] Read more.
The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture radar (SAR) meets the expectations of intended users. In this study, we provide an overview of initial results obtained for three high-priority applications; flood mapping, sea ice analysis, and wetland classification. In our study, the focus is on results obtained using not only linear polarization, but also the adopted Compact Polarimetric (CP) architecture in RCM. Our study shows a promising level of agreement between RCM and RADARSAT-2 performance in flood mapping using dual-polarized HH-HV SAR data over Red River, Manitoba, suggesting smooth continuity between the two satellite missions for operational flood mapping. Visual analysis of coincident RCM CP and RADARSAT-2 dual-polarized HH-HV SAR imagery over the Resolute Passage, Canadian Central Arctic, highlighted an improved contrast between sea ice classes in dry ice winter conditions. A statistical analysis using selected sea ice samples confirmed the increased contrast between thin and both rough and deformed ice in CP SAR. This finding is expected to enhance Canadian Ice Service’s (CIS) operational visual analysis of sea ice in RCM SAR imagery for ice chart production. Object-oriented classification of a wetland area in Newfoundland and Labrador by fusion of RCM dual-polarized VV-VH data and Sentinel-2 optical imagery revealed promising classification results, with an overall accuracy of 91.1% and a kappa coefficient of 0.87. Marsh presented the highest user’s and producer’s accuracies (87.77% and 82.08%, respectively) compared to fog, fen, and swamp. Full article
(This article belongs to the Special Issue RADARSAT Constellation Mission (RCM))
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22 pages, 15869 KiB  
Article
Performance Analysis of Ocean Eddy Detection and Identification by L-Band Compact Polarimetric Synthetic Aperture Radar
by Sijing Shu, Ji Yang, Chuanxun Yang, Hongda Hu, Wenlong Jing, Yiqiang Hu and Yong Li
Remote Sens. 2021, 13(23), 4905; https://doi.org/10.3390/rs13234905 - 03 Dec 2021
Cited by 2 | Viewed by 1777
Abstract
The automatic detection and analysis of ocean eddies has become a popular research topic in physical oceanography during the last few decades. Compact polarimetric synthetic aperture radar (CP SAR), an emerging polarimetric SAR system, can simultaneously acquire richer polarization information of the target [...] Read more.
The automatic detection and analysis of ocean eddies has become a popular research topic in physical oceanography during the last few decades. Compact polarimetric synthetic aperture radar (CP SAR), an emerging polarimetric SAR system, can simultaneously acquire richer polarization information of the target and achieve large bandwidth observations. It has inherent advantages in ocean observation and is bound to become an ideal data source for ocean eddy observation and research. In this study, we simulated the CP data with L-band ALOS PALSAR fully polarimetric data. We assessed the detection and classification potential of ocean eddies from CP SAR by analyzing 50 CP features for 2 types of ocean eddies (“black”and “white”) based on the Euclidean distance and further carried out eddy detection and eddy information extraction experiments. The results showed that among the 50 CP features, the dihedral component power (Pd), shannon entropy (SEI), double bounce (Dbl), Stokes parameters (g0 and g3), eigenvalue (l1), lambda, RVoG parameter (ms), shannon entropy (SE), surface scattering component (Ps), and σHH all performed better for detecting “white” eddies. Moreover, the H-A combination parameter (1mHA), entropy, shannon entropy (SEP, SEI, and SE), probability (p2), polarization degree (m), anisotropy, probability (p1), double bounce (Dbl), H-A combination parameter (H1mA), circular polarization ratio (CPR), and σVV were better CP features for detecting “black” eddies. Full article
(This article belongs to the Special Issue RADARSAT Constellation Mission (RCM))
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17 pages, 17814 KiB  
Communication
Sentinel-1 and RADARSAT Constellation Mission InSAR Assessment of Slope Movements in the Southern Interior of British Columbia, Canada
by Byung-Hun Choe, Andrée Blais-Stevens, Sergey Samsonov and Jonathan Dudley
Remote Sens. 2021, 13(19), 3999; https://doi.org/10.3390/rs13193999 - 06 Oct 2021
Cited by 8 | Viewed by 3070
Abstract
Landslides are the most common natural hazard in British Columbia. The province has recorded the largest number of historical landslide fatalities in Canada, and damage to infrastructure comes at a great cost. In order to understand the potential impacts of landslides, radar remote [...] Read more.
Landslides are the most common natural hazard in British Columbia. The province has recorded the largest number of historical landslide fatalities in Canada, and damage to infrastructure comes at a great cost. In order to understand the potential impacts of landslides, radar remote sensing has become a cost-effective method for detecting downslope movements. This study investigates downslope movements in the Southern Interior of British Columbia, Canada, with Sentinel-1 and RADARSAT Constellation Mission (RCM) interferometric synthetic aperture radar (InSAR) data. The 2-dimensional time-series analysis with Sentinel-1 ascending and descending InSAR pairs from October 2017 to June 2021 observed distinct earthflow movements of up to ~15 cm/year in the east–west direction. The Grinder Creek, Red Mountain, Yalakom River, and Retaskit Creek earthflows previously documented are still active, with east–west movements of ~30 cm over the past four years. New RCM data acquired from June 2020 to September 2020 with a 4-day revisit capability were compared to 12-day Sentinel-1 InSAR pairs. The 4-day RCM InSAR pairs at higher spatial resolution showed better performance by detecting relatively small-sized slope movements within a few hundred meters, which were not clearly observed by Sentinel-1. The temporal variabilities observed from the RCM InSAR showed great potential for observing detailed slope movements within a narrower time window. Full article
(This article belongs to the Special Issue RADARSAT Constellation Mission (RCM))
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23 pages, 7233 KiB  
Article
Compact Polarimetry Response to Modeled Fast Sea Ice Thickness
by Mohammed Dabboor and Mohammed Shokr
Remote Sens. 2020, 12(19), 3240; https://doi.org/10.3390/rs12193240 - 05 Oct 2020
Cited by 8 | Viewed by 2335
Abstract
Compact Polarimetric (CP) Synthetic Aperture Radar (SAR) is expected to gain more and more ground for Earth observation applications in the coming years. This comes in light of the recently launched RADARSAT Constellation Mission (RCM), which uniquely provides CP SAR imagery in operational [...] Read more.
Compact Polarimetric (CP) Synthetic Aperture Radar (SAR) is expected to gain more and more ground for Earth observation applications in the coming years. This comes in light of the recently launched RADARSAT Constellation Mission (RCM), which uniquely provides CP SAR imagery in operational mode. In this study, we present observations about the sensitivity of CP SAR imagery to thickness of thermodynamically-grown fast sea ice during early ice growth (September–December 2017) in the Resolute Bay area, Canadian Central Arctic. Fast ice is most suitable to use for this preliminary study since it exhibits only thermodynamic growth in absence of ice mobility and deformation. Results reveal that ice thickness up to 30 cm can be retrieved using several CP parameters from the tested set. This ice thickness corresponds to the thickness of young ice. We found the surface scattering mechanism to be dominant during the early ice growth, exposing an increasing tendency up to 30 cm thickness with a correlation coefficient with the thickness equal to 0.86. The degree of polarization was found to be the parameter with the highest correlation up to 0.95. While thickness retrieval within the same range is also possible using parameters from Full Polarimetric (FP) SAR parameters as shown in previous studies, the advantage of using CP SAR mode is the much larger swath coverage, which is an operational requirement. Full article
(This article belongs to the Special Issue RADARSAT Constellation Mission (RCM))
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