• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.436-445
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• 2023

Methane (CH₄) emissions from rice paddies are mainly observed using the closed chamber method or the eddy covariance method. In this study, a new observation technique combining a portable gas analyzer (Model LI-7810, LI-COR, Inc., USA) and an automatic opening/closing chamber (Model Smart Chamber, LI-COR, Inc., USA) was introduced based on the strengths and weaknesses of the existing measurement methods. A cylindrical collar was manufactured according to the maximum growth height of rice and used as an auxiliary measurement tool. All types of measured data can be monitored in real time, and CH₄ flux is also calculated simultaneously during the measurement. After the measurement is completed, all the related data can be checked using the software called 'SoilFluxPro'. The biggest advantage of the new observation technique is that time-series changes in greenhouse gas concentrations can be immediately confirmed in the field. It can also be applied to small areas with various treatment conditions, and it is simpler to use and requires less effort for installation and maintenance than the eddy covariance system. However, there are also disadvantages in that the observation system is still expensive, requires specialized knowledge to operate, and requires a lot of manpower to install multiple collars in various observation areas and travel around them to take measurements. It is expected that the new observation technique can make a significant contribution to understanding the CH₄ emission pathways from rice paddies and quantifying the emissions from those pathways.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.398-403
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• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.637-654
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• 2023

In recent years, the number of users has been increasing with the rapid development of earth observation satellites. In response, the Committee on Earth Observation Satellites (CEOS) has been striving to provide user-friendly satellite images by introducing the concept of Analysis Ready Data (ARD) and defining its requirements as CEOS ARD for Land (CARD4L). In ARD, a mask called an Unusable Data Mask (UDM), identifying unnecessary pixels for land analysis, should be provided with a satellite image. UDMs include clouds, cloud shadows, terrain shadows, etc. Terrain shadows are generated in mountainous terrain with large terrain relief, and these areas cause errors in analysis due to their low radiation intensity. previous research on terrain shadow detection focused on detecting terrain shadow pixels to correct terrain shadows. However, this should be replaced by the terrain correction method. Therefore, there is a need to expand the purpose of terrain shadow detection. In this study, to utilize CAS500-4 for forest and agriculture analysis, we extended the scope of the terrain shadow detection to shaded areas. This paper aims to analyze the potential for terrain shadow detection to make a terrain shadow mask for South and North Korea. To detect terrain shadows, we used a Hill-shade algorithm that utilizes the position of the sun and a surface's derivatives, such as slope and aspect. Using RapidEye images with a spatial resolution of 5 meters and Sentinel-2 images with a spatial resolution of 10 meters over the Korean Peninsula, the optimal threshold for shadow determination was confirmed by comparing them with the ground truth. The optimal threshold was used to perform terrain shadow detection, and the results were analyzed. As a qualitative result, it was confirmed that the shape was similar to the ground truth as a whole. In addition, it was confirmed that most of the F1 scores were between 0.8 and 0.94 for all images tested. Based on the results of this study, it was confirmed that automatic terrain shadow detection was well performed throughout the Korean Peninsula.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.152-161
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• 2023

In general, large-capacity hydrogen storage vessels, typically in the form of vertical cylindrical vessels, are constructed using steel materials. These vessels are anchored to foundation slabs that are specially designed to suit the environmental conditions. This anchoring method involves pre-installed anchors on top of the concrete foundation slab. However, it's important to note that such a design can result in concentrated stresses at the anchoring points when external forces, such as seismic events, are at play. This may lead to potential structural damage due to anchor and concrete damage. For this reason, in this study, it selected an vertical hydrogen storage vessel based on site observations and created a 3D finite element model. Artificial seismic motions made following the procedures specified in ICC-ES AC 156, as well as domestic recorded earthquakes with a magnitude greater than 5.0, were applied to analyze the structural behavior and performance of the target structures. Conducting experiments on a structure built to actual scale would be ideal, but due to practical constraints, it proved challenging to execute. Therefore, it opted for an analytical approach to assess the safety of the target structure. Regarding the structural response characteristics, the acceleration induced by seismic motion was observed to amplify by approximately ten times compared to the input seismic motions. Additionally, there was a tendency for a decrease in amplification as the response acceleration was transmitted to the point where the centre of gravity is located. For the vulnerable components, specifically the sub-system (support columns and anchorages), the stress levels were found to satisfy the allowable stress criteria. However, the concrete's tensile strength exhibited only about a 5% margin of safety compared to the allowable stress. This indicates the need for mitigation strategies in addressing these concerns. Based on the research findings presented in this paper, it is anticipated that predictable load information for the design of storage vessels required for future shaking table tests will be provided.

• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1321-1330
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• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.61-67
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• 2023

Heat pipes located underground in urban areas and operated under high temperature and pressure conditions can cause large-scale human and economic damage if damaged. In order to predict damage in advance, damage and construction information of heat pipe are analyzed to derive independent variables that have a correlation with frequency of damage, and a simple regression analysis modified model using each variable is applied to the field. However, as the correlation between independent variables applied to the model increases, the independence between variables is harmed and the reliability of the model decreases. In this study, the independence of the pipe diameter, burial depth, insulation level of monitoring system, and disconnection or short circuit of the detection line, which are judged to be interrelated, was tested to derive a method for combining variables and setting categories necessary to apply to the frequency of damage estimation model. For the test of independence, the continuous variables pipe diameter and burial depth were each converted into three categories, insulation level of monitoring system was converted into two categories, and the categorical variable disconnection or short circuit of the detection line status was kept as two categories. As a result of the test of independence, p-value between pipe diameter and burial depth, level of monitoring system and disconnection or short circuit of the detection line was lower than the significance level (α = 0.05), indicating a large correlation between them. Therefore, the pipe diameter and burial depth were combined into one variable, and the categories of the combined variable were set to 9 considering the previously set categories. The insulation level of monitoring system and the disconnection or short circuit of the detection line were also combined into one variable. Since the insulation level is unreliable when the detection line status is disconnection or short circuit, the categories of the combined variable were set to 3.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.423-446
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• 2023

Shield TBM tunnel linings are segmented into segments and rings. This study investigates the response characteristics of the stress and displacement of the segment lining under seismic waves through modeling that considers the interface behavior between segments by applying a shell interface element to the contact surface between segments and rings. And there is no management criteria for ovaling deformation of segment linings in Korea. So, this study the ovality criteria and meaning of segment lining. The results of study showed that the distribution patterns of stress and displacement under seismic waves were similar between continuous linings and segment linings. However, the maximum values of stress and displacement showed differences from segment linings. The stress distribution of the continuous lining modeled as a shell type has a stress distribution that has continuity in the 3D cylindrical shape, but the segment lining is concentrated outside the segment, and the largest stress occurs at the location where the contact surface between the segment and the ring is concentrated. This intermittent and localized stress distribution shows an increasing as the ovality of the lining increases at seismic waves. The ovality at which the increase in stress distribution begins to show irregularity and localization is about 150‰. Ovality of 150‰ is an unrealistic value that cannot represent actual lining deformation. Therefore, the ovality of the segment lining increase with depth, but it does not have a significant impact on the stability caused by seismic load.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1327-1341
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• 2022

Purpose To evaluate the pattern of use and the perception of digital breast tomosynthesis (DBT) among Korean breast radiologists. Materials and Methods From March 22 to 29, 2021, an online survey comprising 27 questions was sent to members of the Korean Society of Breast Imaging. Questions related to practice characteristics, utilization and perception of DBT, and research interests. Results were analyzed based on factors using logistic regression. Results Overall, 120 of 257 members responded to the survey (response rate, 46.7%), 67 (55.8%) of whom reported using DBT. The overall satisfaction with DBT was 3.31 (1-5 scale). The most-cited DBT advantages were decreased recall rate (55.8%), increased lesion conspicuity (48.3%), and increased cancer detection (45.8%). The most-cited DBT disadvantages were extra cost for patients (46.7%), insufficient calcification characterization (43.3%), insufficient improvement in diagnostic performance (39.2%), and radiation dose (35.8%). Radiologists reported increased storage requirements and interpretation time for barriers to implementing DBT. Conclusion Further improvement of DBT techniques reflecting feedback from the user's perspective will help increase the acceptance of DBT in Korea.