Special Issue "Added-Value SAR Products for the Observation of Coastal Areas"

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

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Andrea Buono
E-Mail Website
Guest Editor
Engineering Department, University of Naples “Parthenope”, 80143 Naples, Italy
Interests: electromagnetic modeling; SAR; polarimetry; ocean; coastal areas
Special Issues and Collections in MDPI journals
Prof. Dr. Weizeng Shao
E-Mail Website
Guest Editor
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
Interests: SAR oceanography; ocean modeling; climatology
Special Issues and Collections in MDPI journals
Dr. Carina Regina de Macedo
E-Mail Website
Guest Editor
Laboratoire d'Océanologie et de Géosciences (LOG), French National Centre for Scientific Research, 62930 Wimereux, France
Interests: electromagnetic modeling; SAR; polarimetry; ocean mesoscale features

Special Issue Information

Dear Colleagues,

Coastal regions represent extremely important areas for the economy, environment and social life. In Europe, about 40% of people live within 50 km of the sea while almost 40% of gross production comes from those regions, which corresponds to approximately 75% of the maritime export volume. Coastal anthropogenic activities such as shipping, resource exploration and extraction, tourism, renewable energy are of paramount importance for human life while putting pressure on local ecosystems that need to be preserved.

Hence, a continuous, updated and synoptic monitoring and mapping of those activities and the impact they have on the coastal ecosystems, even at polar regions, through processes as pollution, coastal erosion and climate change is needed. Within this framework, the use of multi-platform/frequency/polarization synthetic aperture radar (SAR) as well other microwave satellites can provide regional-scale and fine-resolution day and night observations of coastal areas under almost all weather conditions. Currently, the spreading of SAR imagery worldwide has enabled new applications and boosted the development of new models and algorithms to generate added-value products.

Accordingly, in this Special Issue, although the exploitation of SAR measurements for the observation of coastal areas is a well-established methodology, we are seeking the latest research advancements on related topics, including innovative methods, improved models and analysis tools and new added-value products. Hence, the topics of this Special Issue include, but are not limited to, the following subjects:

  • Land use/land cover classification;
  • Extraction and analysis of the coastal profile;
  • Monitoring of anthropogenic targets and critical infrastructures as oil/gas fields, harbors, ships, offshore wind farms, aquaculture, plastic litter;
  • Estimation of sea wind field;
  • Detection of natural targets as icebergs, algal blooms, oil spills, mangroves;
  • Modeling and retrieval of geophysical parameters.

Dr. Andrea Buono
Prof. Dr. Weizeng Shao
Dr. Carina Regina de Macedo
Guest Editors

Manuscript Submission Information

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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 2400 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.


  • SAR
  • target detection
  • classification
  • ocean
  • wind
  • modeling
  • retrieval
  • polarimetry

Published Papers (1 paper)

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Application of SAR Data for Tropical Cyclone Intensity Parameters Retrieval and Symmetric Wind Field Model Development
Remote Sens. 2021, 13(15), 2902; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13152902 - 23 Jul 2021
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The spaceborne synthetic aperture radar (SAR) is an effective tool to observe tropical cyclone (TC) wind fields at very high spatial resolutions. TC wind speeds can be retrieved from cross-polarization signals without wind direction inputs. This paper proposed methodologies to retrieve TC intensity [...] Read more.
The spaceborne synthetic aperture radar (SAR) is an effective tool to observe tropical cyclone (TC) wind fields at very high spatial resolutions. TC wind speeds can be retrieved from cross-polarization signals without wind direction inputs. This paper proposed methodologies to retrieve TC intensity parameters; for example, surface maximum wind speed, TC fullness (TCF) and central surface pressure from the European Space Agency Sentinel-1 Extra Wide swath mode cross-polarization data. First, the MS1A geophysical model function was modified from 6 to 69 m/s, based on three TC samples’ SAR images and the collocated National Oceanic and Atmospheric Administration stepped frequency microwave radiometer wind speed measurements. Second, we retrieved the wind fields and maximum wind speeds of 42 TC samples up to category 5 acquired in the last five years, using the modified MS1A model. Third, the TCF values and central surface pressures were calculated from the 1-km wind retrievals, according to the radial curve fitting of wind speeds and two hurricane wind-pressure models. Three intensity parameters were found to be dependent upon each other. Compared with the best-track data, the averaged bias, correlation coefficient (Cor) and root mean-square error (RMSE) of the SAR-retrieved maximum wind speeds were –3.91 m/s, 0.88 and 7.99 m/s respectively, showing a better result than the retrievals before modification. For central pressure, the averaged bias, Cor and RMSE were 1.17 mb, 0.77 and 21.29 mb and respectively, indicating the accuracy of the proposed methodology for pressure retrieval. Finally, a new symmetric TC wind field model was developed with the fitting function of the TCF values and maximum wind speeds, radial wind curve and the Rankine Vortex model. By this model, TC wind field can be simulated just using the maximum wind speed and the radius of maximum wind speed. Compared with wind retrievals, averaged absolute bias and averaged RMSE of all samples’ wind fields simulated by the new model were smaller than those of the Rankine Vortex model. Full article
(This article belongs to the Special Issue Added-Value SAR Products for the Observation of Coastal Areas)
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