GEO DATA

Original Paper

Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates: Jinku Park, Sungjae Lee, Jeong-Hoon Kim, Hyun-Cheol Kim; GEO DATA. 2023;5(1):8-14. Published online March 28, 2023; DOI: https://doi.org/10.22761/GD.2023.0002

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Abstract PDF: This study, focusing on the Antarctic polynyas, performed the imputation of chlorophyll-a concentration (Chl-a) dataset, which is one of the ocean color products mainly used for estimating primary productivity, using the Data Interpolating Empirical Orthogonal Function method and constructed accurate time-series data that excludes as much uncertainty as possible in long-term variability studies due to missing data. The polynya regions were classified into a total of 23 zones through quantitative criterions, and the statistical accuracy of imputation performance was 0.89 for R2 and 0.42, 0.24, and 0.15 for root mean square error, mean squared error, mean absolute error, respectively, on average, showing the ability to perform generally accurate reconstruction. Finally, the reconstructed Chl-a data showed a relatively stable fluctuation compared with standard satellite Chl-a data, and tended to be underestimated due to the expansion of the observable regions. We expect that securing these relatively stable and accurate estimates will be significantly different from the time-series data composed of standard Chl-a estimates, enabling more accurate variability and trend analysis.

Articles

The Map Data of BRDF-Adjusted Surface Reflectance from GOCI Geostationary Satellite Imagery over Korean Peninsula: Jong-Min Yeom; GEO DATA. 2021;3(4):66-70. Published online December 31, 2021; DOI: https://doi.org/10.22761/DJ2021.3.4.006

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Abstract PDF: In this study, the spatial maps of the BRDF (Bidirectional Reflectance Distribution Function) adjusted surface reflectance (SR) were estimated by using the Geostationary Ocean Color Imager (GOCI) mounted on the Communication, Ocean and Meteorological Satellite (COMS) over the Korean Peninsula. The BRDF-Adjusted surface Reflectance (BAR) is a more effective indicator that not only quantitatively identifies the growth characteristics of vegetation, but also corrects the bidirectional error in the time series observation characteristics, because the surface reflectance is changed according to the solar altitude during the daytime period. Therefore, this BAR products have high data utilization in various fields such as agriculture, environment, land surface information, and atmosphere. In this study, BRDF-adjusted surface reflectance maps were calculated for the Korean peninsula from April 2011 to December 2012 with hourly temporal resolution from 9 a.m. to 4 p.m. For the BAR surface reflectance, the spatial observation range is from latitude 34° N to 39 °N and longitude 125 ° E to 130 ° E, and the spatial resolution is 500 m. The semi-empirical BRDF model was used to calculate the BRDF-adjusted surface reflectance, and the radiometric characteristics of surface reflectance were decomposed into isotropic scattering, geometric scattering, and volumetric scattering. For this model simulation, at least 7 clear pixels are required to fit BRDF model. In this study, unlike the Nadir BRDF-Adjusted surface Reflectance (NBAR) calculation method which was calculated from the existing polar orbiting satellites, semi-empirical BRDF modeling was performed with a value fixed to the satellite viewing angle for each pixel since geostationary satellites of GOCI are difficult to observe in the nadir direction unlike polar satellites. It is more effective to perform BRDF correction by fixing them at the viewing angle in the case of GOCI geostationary satellite.

Reconstruction of Satellite Chlorophyll-a Concentration in the Southwestern East Sea using Imputation Method: Jinku Park, Sungjae Lee, Hyun-Cheol Kim; GEO DATA. 2021;3(4):11-17. Published online December 31, 2021; DOI: https://doi.org/10.22761/DJ2021.3.4.002

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Abstract PDF: The chlorophyll-a concentration (CHL) data observed with the ocean color sensors have been widely used in the various studies related to phytoplankton. However, irregularly distributed missing data induced by clouds, a unique nature of optics, can cause large uncertainty, and a solution to this missing issue has been continuously demanded until now. We investigated the applicability of the data interpolating empirical orthogonal function and evaluated the reconstruction results in the southwestern East Sea. A total of 311 decomposed modes were used, showing a coefficient of determination of about 0.86 and a root mean square error of 0.37 mg m⁻³, compared to the truth data. Overall, it was confirmed that the observed CHL was overestimated compared to the reconstructed CHL when the spatio-temporal average was taken.

In-situ Measurement of the Arctic Ocean for Optical Property Analysis During 2019 Cruise: Sungjae Lee, Hyun-Cheol Kim; GEO DATA. 2020;2(2):63-70. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.009

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Abstract PDF: The Arctic issue has increased due to global warming. The Arctic is losing the role of cooling because reducing sea ice by warming on the Arctic, which is changing the energy balance on the Earth system. Change of Arctic ocean, atmosphere, and cryosphere influence on an ecosystem of Arctic as well. These changes are monitoring by remote sensing due to the Arctic is difficult for human access, and where is a wide area. However, a low solar altitude on the Arctic limits Ocean Color Algorithms applies to the Arctic because most ocean color algorithms are based on empirical data in the mid-latitude. Continuous data sampling on the Arctic ocean is the best way to improve and develop a suitable ocean color algorithm for the Arctic. This paper aims to report ocean observation data acquired by Ice-Breaker research vessel Araon during the summer Arctic expedition of 2019. Acquired samples are chlorophyll-a, suspended sediment concentration, in-situ measured ocean optical properties. Sampled data showed that there is a significant effect of dissolved organic matter in its inherent optical properties. We use these data for the aims of improving and develop ocean color algorithms in the Arctic.

Above water remote sensing reflectance dataset on the coastal waters of California and Korea: Jee-Eun Min, Jeong-Eon Moon, Jong-Kuk Choi, Liane Guild, Joo-Hyung Ryu; GEO DATA. 2020;2(2):5-13. Published online December 30, 2020; DOI: https://doi.org/10.22761/DJ2020.2.2.002

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Abstract PDF: Remote sensing reflectance (R_rs) is a fundamental data of ocean color remote sensing that is used as an input data for algorithm development. In this study, the Rrs spectra acquired from the coast of Korea and California, on the opposite side of the Pacific Ocean, were analyzed and compared. The waters of Gyeonggi Bay and Mokpo had a similar spectrum to those of the waters inside of the San Francisco Bay, although the waters of each region had different characteristics. The South Sea in Korea showed similar spectral characteristics on the waters of Monterey Bay and outside of the San Francisco Bay in California. The upward slope of the Rrs spectra in the range of 400 to 600 nm obtained from the inside of the San Francisco Bay was higher than the coastal waters on the Gyeonggi Bay and Mokpo in Korea. The Rrs spectra showing peaks on 580 nm and 680 ~ 700 nm due to chlorophyll were similarly observed in the South and East Seas of Korea, and the coastal waters of Monterey Bay and the outside of the San Francisco Bay in California.

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