• 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.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.43-60
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• 2023

Although the importance of starting a business is being emphasized, it is not easy for a start-up to survive. Therefore, it is necessary to come up with a plan to strengthen startup satisfaction and improve the survival rate of startup companies. In this study, we examined the impact of start-up motivation, start-up capabilities, and start-up passion of start-up companies on start-up satisfaction, as well as the moderating effect according to the founding type of general start-up companies and startups. Entrepreneurship motivation was divided into self-actualization motivation and pro-social motivation. Entrepreneurship capabilities were divided into marketing capabilities and experience capabilities. Entrepreneurship passion was divided into harmonious passion and obsessive passion. Empirical analysis was conducted by receiving surveys from 361 managers of general and startup companies within 7 years of founding their businesses online and offline. As a result, self-actualization motivation, pro-social motivation, marketing competency, experiential competency, and harmonious passion had a significant positive (+) effect on startup satisfaction. However, obsessive passion did not have a significant effect. In addition, the magnitude of influence on startup satisfaction appeared in the following order: harmonious passion, marketing competency, self-actualization motivation, pro-social motivation, and experiential competency. The moderating effect according to the type of founding of general start-ups and startups was found in pro-social motivation, experience competency, and passion for harmony. However, there was no significant moderating effect between self-actualization motivation, marketing competency, obsessive passion, and entrepreneurship satisfaction. This study presented academic implications that harmonious passion and marketing capabilities are important factors in improving startup satisfaction. In addition, practical and policy implications were presented, including the need for programs to support the psychological stability of startup business owners, strengthening startup capabilities through experts, and strengthening startup education programs that can foster self-actualization motivation and pro-social motivation.

• Land and Housing Review
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• v.14 no.4
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• pp.77-93
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• 2023

The COVID-19 pandemic has brought about significant social changes through government prevention and control measures, changes in people's risk perceptions, and lifestyle changes. In response, urban inhabitants changed their behaviors significantly, including their preferences for transportation modes and urban spaces in response to government quarantine policies and concerns over the potential risk of infection in urban spaces. These changes may have long-lasting effects on urban spaces beyond the COVID-19 pandemic or they may evolve and develop new forms. Therefore, this study aims to explore the potential for urban spaces to adapt to the present and future pandemics by examining changes in urban residents' preferences in travel modes and urban space use due to the COVID-19 pandemic. This study found that overall preferences for travel modes and urban spaces significantly differ between the pre-pandemic, pandemic, and post-pandemic periods. During the pandemic, preferences for travel modes and urban spaces has decreased, except for privately owned vehicles and green spaces, which are perceived to be safe from transmission, show more favorable than others. Post-pandemic preferences for travel modes and urban spaces are less favorable than pre-pandemic with urban spaces being five times less favorable than transportation. Although green spaces and medical facilities that were positively perceived during the pandemic are expected to return to the pre-pandemic preference level, other factors of urban spaces are facing a new-normal. The findings suggest that the COVID-19 pandemic has had a significant impact on urban residents' preferences for travel modes and urban space use. Understanding these changes is crucial for developing strategies to adapt to present and future pandemics and improve urban resilience.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• 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.

• Journal of Public Diplomacy
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• v.2 no.2
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• pp.27-52
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• 2022

Objectives: The neighboring countries of South Korea and Japan in Northeast Asia have interacted in both positive and negative ways, at times as close partners and other times adversaries, throughout their long and thorny history of extensive dynamics. The controversial dispute over Dokdo is one of the most critical issues evoking harsh tensions and arguments asserting wholly opposite claims. Dokdo is a small island between two coastal states, but significant in terms of territorial, botanical, and marine resources, and thus ownership of the island has become a point of conflict accompanied by a troubled history. But why has Dokdo been a source of conflicts and how should the controversial Dokdo issue be addressed in a way that fosters positive influence and co-prosperity? Methods: This study provides comprehensive and critical insights from a wealth of previous research and strategic suggestions for the Korean government. It utilizes the three perspectives of historical documents and political context, international regulations and legal frames, and public diplomacy. Furthermore, it applies these resources to negotiation theories and strategies to propose reasonable solutions. Results: This study suggests that it is important for Korea and Japan to try to build mutual trust through more active communication and interaction in order to understand each other before attempting to create a formal resolution via negotiation. In addition to these efforts, Korea needs to be ready for the inevitable need to take decisive action in terms of negotiation, using analytic and efficient strategies. The study proposes three solutions: 1) Strong Action Strategy, 2) International Legal Strategy, and 3) Public Diplomacy Strategy. Conclusions: From the perspective of public diplomacy, the Dokdo issue needs to be converted from a symbol of conflicts between Korea and Japan into a symbol of peace and co-prosperity. In addition to promoting a positive relationship between the two states, it can also contribute to the security environment of the Northeast Asian region and global peace.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.639-652
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• 2023

The fundamental background behind the introduction of the fishing vessel system is to allow petty small fishers to engage in pure fishery business activities with fishing vessels during normal times and engage in fishing vessel business only during specific periods (closed fishing season, etc.) thereby granting a qualification as an auxiliary tool for the economic activities of petty small fishers. In addition, fishing boats are allowed to engage in excursion ship activities using fishing vessels registered under the Fishing Vessels Act, the form of fishing vessels should also have a general and universal structure that is practically easy to engage in fishing activities in the field in accordance with the relevant regulations. However, most fishing vessel proprietors are currently focusing only on increasing income, and rather than building fishing vessels in a reasonable form suitable for the original purpose of general fishing vessels, they prefer an abnormal hull form equivalent to expediency, that is biased hull structure biased toward the fishing vessel business. As a result, it is causing serious problems in safety management as well as conflict [damaging relative equity in government support measures (tax-free oil supply, etc.), and depletion of livelihood-type fish stocks] with fishing vessel forces who consider the fishing vessel business only to be a part of the side job among all fishery business activities. Meanwhile, the most fundamental cause of this problem is that the current Fishing Management and Promotion Act, limits the concept of fishing vessels to fishing vessels registered under the Fishing Vessels Act, and applies survey standards accordingly. Accordingly, in this study, through analysis of the distribution status of fishing vessels, structural characteristics, operation status of fishing vessels, and the government's fishing promotion policies, etc., the relevant laws (regulations) have been reorganized to suit the current reality of the concept of fishing vessels to separate the current fishing vessel from fishing vessels and operate it as a fishing-only vessel.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.207-217
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• 2023

This study was conducted to investigate the current status of seagrass species in the Nakdong River estuary from May to June 2023. To survey the seagrass habitat area, the Nakdong River estuary was divided into seven zones. Aerial photography using drones was conducted to find seagrass areas, GPS tracking was carried out on foot in the intertidal zone and by boat and SCUBA diving in the subtidal zone. To analyze the seagrass status, we measured the morphological characteristics, shoot density, and biomass of representative seagrass species in each zone. Four seagrass species were found in this area: Zostera japonica, Z. marina, Ruppia maritima, and Phyllospadix japonicus. The distribution areas of each species was 338.2 ha, 92.9 ha, 0.9 ha, and 1.4 ha, respectively, with a total area of 432.5 ha. Z. japonica was widely distributed in most of the tidal flats and mudflats of the Nakdong River estuary, while Z. marina was restricted to Nulcha-do, Jinu-do, and Dadae-dong. R. maritima occurred within the habitat of Z. japonica in Eulsukdo and Myeongji mudflats, and P. japonicus inhabited rocky areas in Dadae-dong. The shoot density of each species was 4,575.8±338.3 shoots m^-2, 244.8±12.0 shoots m^-2, 11,302.1±290.0 shoots m^-2, and 2862.5±153.5 shoots m^-2, respectively. The biomass of each species was 239.7±18.5 gDW m^-2, 362.3±20.5 gDW m^-2, 33.3±1.2 gDW m^-2, and 1,290.0±37.0 gDW m^-2, respectively. The results of this study revealed that Z. japonica was dominant in the Nakdong River estuary. In particular, Z. japonica habitats of Eulsukdo, Daema-deung, and Myeongji mudflats were identified as the largest in Korea. The Nakdong River estuary is an important site of ecological, environmental, and economic value, and will require continuous investigation and management of the native seagrasses.