Special Issue "Ocean Monitoring from Geostationary Platform"

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

Deadline for manuscript submissions: 31 August 2022 | Viewed by 1223

Special Issue Editors

Dr. JongKuk Choi
E-Mail Website
Guest Editor
Korea Institute of Ocean Science & Technology, 385, Haeyang-ro, Yeongdo-gu, Busan Metropolitan City, Korea
Interests: application of GOCI to monitoring the marine environment
Prof. Dr. Wonkook Kim
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Pusan National University, 2 Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan Metropolitan City, Korea
Interests: ocean color; quantitative remote sensing; hyperspectral sensing

Special Issue Information

Dear Colleagues,

Since SeaSat and Tiros-N, the first ocean satellites that carry microwave, radar, and optical sensors such as AVHRR and CZCS, launched in 1978, the space-borne observation capability for oceans has remarkably advanced, making the synoptic data sets indispensable in all fields of oceanography and climate studies. While polar orbiting satellites have shown great success in capturing oceanic phenomena of global scale, geostationary satellites such as COMS, Geo-KOMPSAT-2, GOES, Himawari-8/-9, Insat, and the Fengyun series demonstrated unique benefits in ocean monitoring, providing high observation frequencies for designated areas. The merits of geostationary platforms will also be further exploited in upcoming missions such as GEO-XO by NOAA and GLIMR by NASA. 

This Special Issue endeavors to assemble novel studies that utilize advanced remote sensing technology to monitor ocean surface based upon the data from geostationary platforms. Numerous studies already demonstrated that the geostationary platforms have great advantages in monitoring short-term variations in the ocean, such as dynamics in suspended sediments, migration of harmful algal blooms, low salinity water intrusion, and formation of oceanic eddies and filaments.  The subjects of this issue include, but are not limited to

  • Investigation of local or regional oceanic phenomena of high temporal frequency, conducted with geostationary platforms such as high towers, hoverflies (tethered drone), helikites, and geostationary satellites.
  • Potentials and suggestions of new observation concepts for geostationary platforms
  • Challenges in data processing of geostationary satellite data caused by, for example, varying satellite and sun geometry, spherical atmosphere, etc.
  • New applications or products derived from geostationary satellites
  • Methodology and experiments for calibration and validation of data from geostationary platforms
  • Synergistic fusion with polar-orbiting satellite data or with any other physical models such as ocean current simulation, for a particular oceanic phenomenon

Dr. JongKuk Choi
Prof. Dr. Wonkook Kim
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 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.


  • Satellite-based ocean monitoring
  • Geostationary satellite
  • Diurnal variation
  • High temporal frequency

Published Papers (1 paper)

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Decadal Measurements of the First Geostationary Ocean Color Satellite (GOCI) Compared with MODIS and VIIRS Data
Remote Sens. 2022, 14(1), 72; https://doi.org/10.3390/rs14010072 - 24 Dec 2021
Cited by 1 | Viewed by 850
The first geostationary ocean color data from the Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) have been accumulating for more than ten years from 2010. This study performs a multi-year quality assessment of GOCI chlorophyll-a (Chl-a) and [...] Read more.
The first geostationary ocean color data from the Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) have been accumulating for more than ten years from 2010. This study performs a multi-year quality assessment of GOCI chlorophyll-a (Chl-a) and radiometric data for 2012–2021 with an advanced atmospheric correction technique and a regionally specialized Chl-a algorithm. We examine the consistency and stability of GOCI, Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) level 2 products in terms of annual and seasonal climatology, two-dimensional frequency distribution, and multi-year time series. Overall, the GOCI agrees well with MODIS and VIIRS on annual and seasonal variability in Chl-a, as the central biological pattern of the most transparent waters over the western North Pacific, productive waters over the East Sea, and turbid waters over the Yellow Sea are reasonably represented. Overall, an excellent agreement is remarkable for western North Pacific oligotrophic waters (with a correlation higher than 0.91 for Chl-a and 0.96 for band-ratio). However, the sporadic springtime overestimation of MODIS Chl-a values compared with others is notable over the Yellow Sea and East Sea due to the underestimation of MODIS blue-green band ratios for moderate-high aerosol optical depth. The persistent underestimation of VIIRS Chl-a values compared with GOCI and MODIS occurs due to inherent sensor calibration differences. In addition, the artificially increasing trends in GOCI Chl-a (+0.48 mg m−3 per 9 years) arise by the decreasing trends in the band ratios. However, decreasing Chl-a trends in MODIS and VIIRS (−0.09 and −0.08 mg m−3, respectively) are reasonable in response to increasing sea surface temperature. The results indicate GOCI sensor degradation in the late mission period. The long-term application of the GOCI data should be done with a caveat, however; planned adjustments to GOCI calibration (2022) in the following GOCI-II satellite will essentially eliminate the bias in Chl-a trends. Full article
(This article belongs to the Special Issue Ocean Monitoring from Geostationary Platform)
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