• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1553-1563
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• 2023

The Geostationary Ocean Color Imager-II (GOCI-II) is a satellite designed for ocean color observation, covering the Northeast Asian region and the entire disk of the Earth. It commenced operations in 2020, succeeding its predecessor, GOCI, which had been active for the previous decade. In this study, we aimed to enhance the atmospheric correction algorithm, a critical step in producing satellite-based ocean color data, by performing cross-calibration on the GOCI-II near-infrared (NIR) band using the GOCI NIR band. To achieve this, we conducted a cross-calibration study on the top-of-atmosphere (TOA) radiance of the NIR band and derived a vicarious calibration gain for two NIR bands (745 and 865 nm). As a result of applying this gain, the offset of two sensors decreased and the ratio approached 1. It shows that consistency of two sensors was improved. Also, the Rayleigh-corrected reflectance at 745 nm and 865 nm increased by 5.62% and 9.52%, respectively. This alteration had implications for the ratio of Rayleigh-corrected reflectance at these wavelengths, potentially impacting the atmospheric correction results across all spectral bands, particularly during the aerosol reflectance correction process within the atmospheric correction algorithm. Due to the limited overlapping operational period of GOCI and GOCI-II satellites, we only used data from March 2021. Nevertheless, we anticipate further enhancements through ongoing cross-calibration research with other satellites in the future. Additionally, it is essential to apply the vicarious calibration gain derived for the NIR band in this study to perform vicarious calibration for the visible channels and assess its impact on the accuracy of the ocean color products.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1635-1650
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• 2023

Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m^-3, and primary production of 580.96-1574.13 mg C m^-2 day^-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1097-1109
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• 2023

Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.188-196
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• 2023

Wheat (Triticum aestivum L.) is an important crop in Korea, with a per capita consumption of 31.6 kg in 2019. In the southern region, wheat is grown after paddy rice, and it is harvested during the rainy season in mid-June. This timing, in combination with high humidity and untimely rainfall, activates the enzyme alpha-amylase, which breaks down starch in the wheat grains. As a result, sprouted grains have lower quality and value for flour. However, seeds that absorb water before sprouting are expected to maintain better quality. The aim of the study was to identify the critical period during wheat maturation when rainfall has the greatest impact on grain quality, to prevent price declines due to quality deterioration. Two wheat cultivars, Jokyoung and Hwanggeumal, were grown in a speed breeding room, and artificial rainfall was applied at different times after heading (30, 35, 40, 45, 50, and 55 days). The proportion of vitreous grains decreased from 40 to 55 days after heading (DAH). Both cultivars had chalky grain sections from 35 DAH, with Hwanggeumal having a higher proportion of vitreous grains. Starch degradation was observed using FE-SEM (Field Emission Scanning Electron Microscope) at 40 DAH for Jokyoung and 50 DAH for Hwanggeumal. Color measurements indicated increased L and E values from 40 DAH, with rain treatment at 55 DAH leading to a significant increase in L values for both cultivars. Ash content increased at 45 DAH, whereas SDSS decreased at 35 DAH. Overall, grain quality from 40 DAH until harvest was found to be affected to the greatest extent by direct exposure of the spikes to moisture. Red wheat showed better quality than white wheat. These findings have implications for the cultivation of high-quality wheat and can guide future research efforts in this area.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.573-588
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• 2023

Purpose: This study aimed to examine social networking service (SNS) use and recommended information utilization (SURU) according to the food-related lifestyles (FRLs) of consumers and analyze how the interaction between the FRL and SURU affects the practice of eating alone and visiting restaurants. Methods: Data on 4,624 adults in their 20s to 50s were collected from the 2021 Consumer Behavior Survey for Food. Statistical methods included factor analysis, K-means cluster analysis, the complex samples general linear model, the complex samples Rao-Scott χ² test, and the general linear model. Results: The following three factors were extracted from the FRL data: Convenience pursuit, rational consumption pursuit, and gastronomy pursuit, and the subjects were classified into three groups, namely the rational consumption, convenient gastronomy, and smart gourmet groups. An examination of the difference in SURU according to the FRL showed that the smart gourmet group had the highest score. The result of analyzing the effects of the FRL and SURU on eating alone revealed that both the main effect and the interaction effect were significant (p < 0.01, p < 0.001). The higher the SURU, the higher the frequency of eating alone in the convenience pursuit, and gastronomy pursuit groups. The main and interaction effects of the FRL and SURU on the frequency of eating out were also significant (p < 0.01, p < 0.001). In all the FRL groups, the higher the SURU level, the higher the frequency of visiting restaurants. Specifically, the two groups with convenience and gastronomic tendencies showed a steeper increase. Conclusion: This study provides important basic data for research on consumer behavior related to food SNS, market segmentation of restaurant consumers, and development of marketing strategies using SNS in the future.

• The Journal of Internal Korean Medicine
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• v.44 no.4
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• pp.726-740
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• 2023

Objectives: This review investigated the research on warm herbal foot bath therapy (WHFT) for insomnia. Methods: A search was conducted on the China National Knowledge Infrastructure (CNKI) database to collect relevant studies published up to August 29, 2023. Randomized controlled trials (RCTs) comparing WHFT and sleeping pills in patients with insomnia were included. The methodological quality of the included studies was assessed using the Cochrane risk-of-bias assessment tool. The results of the meta-analysis were presented as risk ratios (RRs) or mean differences (MDs) and their 95% confidence intervals (CIs). Results: A total of 11 RCTs were included. WHFT as monotherapy resulted in a significantly higher total effective rate (TER) (RR, 1.25; 95% CI, 1.15 to 1.36; I²=25%) and an improved Pittsburgh Sleep Quality Index (PSQI) global sore (MD, -3.10; 95% CI, -4.24 to -1.95; I²=73%) compared to benzodiazepines. Additionally, WHFT as a combined therapy with benzodiazepines resulted in a significantly higher TER (RR, 1.15; 95% CI, 1.04 to 1.27; I²=0%) and an improved PSQI global score (MD, -2.23; 95% CI, -4.09 to -0.38; I²=80%) compared to benzodiazepines alone. In network analysis visualizing the components of HWFT, four clusters were discovered, and Polygoni Multiflori Ramuls and Ziziphi Spinosae Semen were the key herbs used in WHFT. Overall, the methodological quality of the included studies was poor. Conclusions: There was limited evidence that WHFT as a monotherapy or combined therapy was effective in improving insomnia. The findings can be used as basic data for future WHFT research in South Korea.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.187-195
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• 2023

Almost all of the water from agricultural dams located to the upper of the Yeongsan river is supplied as irrigation water for farmland and thus is not discharged to the main stream of the river. Also, most of the irrigation water does not return to the river after use, adding to the lack of flow in the main stream. As a result, the water quality and aquatic health of the river have become the poorest among the four major rivers in Korea. Therefore, in this study, several strategies for water quality improvement of the river were developed considering pollution reduction and flow rate increase, and their effect analysis was performed using a water quality model. The results of this study showed that the target water quality of the Yeongsan river could be achieved if flow increase strategies (FISs) are intensively pursued in parallel with pollution reduction. The reason is because the water quality of the river has been steadily improved through pollution reduction but this method is now nearing the limit. In addition, rainfall-related FISs such as dam construction and water distribution adjustment may be less effective or lost if a megadrought continues due to climate change and then rainfall does not occur for a long time. Therefore, in the future, if the application conditions for the FISs are similar, the seawater desalination facility, which is independent of rainfall, should be considered as the priority installation target among the FISs. The reason is that seawater desalination facilities can replace the water supply function of dams, which are difficult to newly build in Korea, and can be useful as a climate change adaptation facility by preventing water-related disasters in the event of a long-term megadrought.