Publications

Shin, J; Jo, YH; Khim, BK; Kim, SM (2024). U-Net Super-Resolution Model of GOCI to GOCI-II Image Conversion. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 62, 5608612.

Abstract
The use of ocean color sensors presents limitations to monitoring coastal environmental changes and capturing fine spatial features below 1 km due to low spatial (0.5-1 km) and temporal (1 day) resolutions. The geostationary ocean color imager (GOCI)-II, launched on February 18, 2020, is a follow-up mission to GOCI, operated from June 27, 2010 to March 31, 2021. GOCI-II imagery, with a spatial resolution of 250 m, detects more detailed spatial structures of ocean dynamics compared to GOCI with a spatial resolution of 500 m. This study aims to develop a U-Net super-resolution (SR) model to enhance the GOCI remote-sensing reflectance ( R-rs ) imagery to the same spatial resolution as GOCI-II. The U-Net model is trained with eight paired bands (412, 443, 490, 555, 660, 680, 745, and 865 nm) of GOCI and GOCI-II R-rs around the waters of the Korean Peninsula. The consistency level between GOCI and GOCI-II images indicated GOCI sensor degradation, especially in the blue bands, during its last mission period from December 2020 to March 2021. Through quantitative and qualitative evaluations, we found that the U-Net R-rs image had greater spectral information with higher consistency compared to the G1-bicubic image by bicubic interpolation of GOCI. In particular, the U-Net results improved the consistency in the blue bands (412, 443, and 490 nm). Qualitative evaluations also showed that U-Net corrected the blue band underestimation in degraded GOCI images. In addition, chlorophyll-a concentration (CHL) map from the U-Net R-rs not only simulated spatial patterns, similar to GOCI-II CHL map, but also corrected the overestimated GOCI CHL map. The U-Net SR model may help to produce more reliable and fine-scale R-rs products from GOCI similar to those of GOCI-II, and to enable long-term ocean color monitoring around the waters of the Korean Peninsula.

DOI:
10.1109/TGRS.2024.3361854

ISSN:
1558-0644