• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.131-141
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• 2023

Changes in consumer needs and behaviors according to lifestyle changes lead to consumption culture, affecting the automobile market. However, research and research to provide options tailored to the lifestyle of consumers in related markets are still insufficient. Focusing on pickup truck accessories applied to pickup trucks that reflect lifestyle the most among vehicle types, this study first examined the theoretical background of the aftermarket market and lifestyle of pickup trucks. Second, through image mapping, the market possibilities and opportunity factors of pickup trucks were discovered through market size analysis and possibilities, and through this, user types could be classified. Third, interviews were conducted with those representing user types, the contents were organized, and interviews were conducted centering on related groups to create a persona of a user group, and what needs each group's persona wanted. Finally, a design concept suitable for the issue keywords and insights derived for each user lifestyle type was presented. In this study, the user type was divided into ① outdoor activity type, ② hobby activity type, and ③ small-scale work type, and a design case study was conducted by applying the concept suitable for the keyword for each group. For the outdoor activity type, a variable storage structure and a living space-type accessory design were presented, and for the hobby type, a modular decktop design and a sports coupe-type hardtop design were presented. For the small business type, a partition that is easy to fix the load and a stepper design that is easy to board the cargo box were presented. It is expected that the size of the pickup truck aftermarket will be expanded by diversifying the option designs that users want by lifestyle by applying them to the development of pickup truck accessories that fit the lifestyle of pickup truck users in the automobile market, which is currently mass customized.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.683-701
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• 2023

Purpose: The purpose of the study was to analyze the status of dietary behavior and nutrition intakes according to the gender and the level of physical activity of adolescents. Methods: Data from 659 adolescents aged 13 to 18 years who participated in the Korea National Health and Nutrition Examination Survey (2017-2018) were analyzed. Collected data were analyzed using complex sampling data analysis with SPSS v. 27.0. Results: The adolescents were categorized into three groups based on their physical activity as follows: The first group with high physical activity (8.9%), a second group with normal physical activity (29.7%), and a third group without physical activity (61.4%). Boys showed significantly higher physical activity than the girls. Adolescents with high physical activity had a significantly lower body mass index than adolescents without physical activity, but their meal regularity, subjective health status, and recognition of body image were significantly higher. In terms of biochemical factors, adolescents with high physical activity had lower triglycerides and cholesterol than adolescents without physical activity, while hemoglobin and hematocrit were significantly higher. In addition, the intakes of energy, carbohydrates, proteins, fat, vitamin B₁, niacin, calcium, phosphorus, sodium, potassium, iron increased significantly as adolescents' physical activity increased. Conclusion: The physical activity of adolescents had a positive effect on dietary behavior, lifestyle, and nutritional factors. Therefore, it is necessary to increase participation in physical classes in schools and develop various programs considering the level of physical activity among adolescents.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.521-535
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• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.851-857
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• 2023

The purpose of this study is to investigate the effect of changes in collimation size and sub ROI on exposure index(EI) in hand radiography, present collimation size and EI suitable for average hand size of Koreans, and present the effect of changes in sub ROI on EI. The subjects of this study were hand-wrist phantom, and the exposure conditions were set to 55 kVp, 125, mA, and 6.25 mAs, and source to image receptor distance was applied to 110 cm. Based on the vendor recommended sub-ROI (18.7" × 18.7", 8" × 10", 8" × 7.4", 6" × 7.4")and the textbook's recommended sub-ROI 8" × 10", each obtaining 30 images, and comparing the EI shown in the equipment. The EI according to the change in the size of the collimation were 1663.7±4.52, 8"×10" is 1489.1±4.49, 8"×7.4" is 1716.9±3.00, 6"×7.4" is 168.7±3.66 for each EI, and the average value of each value was statistically significant. The average EI according to the sub ROI change was 1489.1±4.49 for SS, LS was 1694.8±5.19 for AEC, 2052.9±5.96, VR was 1548.3±3.20, and HR was 1663.2±4.33. The appropriate field size considering the hand size of Koreans was found to be 8"×7.4". In addition, when the field size increases based on the generally known field size (8"×10") during hand radiography, the EI value changes from a maximum of 15% to a minimum of 11%, and the sub ROI shape based on sub ROI 'SS' Depending on the change, the EI value increased from a maximum of 37% to a minimum of 3%.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Korean Journal of Culture and Social Issue
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• v.10 no.3
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• pp.103-129
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• 2004

This article examines the Korean adolescents and adults' social representation and trust of Korean society and people using indigenous psychological analysis. Respondents were asked to write in an open-ended questionnaire their perception of the following five aspects: Korean politics, economy, society, culture and people. They were then asked to report why they trust or distrust Korean society. A total of 1,064 respondents (218 middle school students, 200 university students, 218 fathers of the middle school students, 218 mothers of the middle school students, and 210 teachers) completed a questionnaire developed by the present researchers. The data were collected during April to June, 2003. The results indicate that 94.5% of Koreans view the existing political system and politicians as being corrupt, inept, factional, and lacking in integrity. A vast majority (84.9%) recognize the existence of systemic problems in the Korean economy. A total of 78.2% see problems in Korean society being dominated by selfishness, factionalism, conservatism, and social uncertainty. For Korean culture, a majority of respondents report being proud of its cultural tradition, accomplishment, and creativity. At the same time, 45.7% report loss of cultural identity and pride due to external influences. More than half of the respondents report negative aspects of Korean people (i.e., selfish, lack of morality, rushed, and overly focused on their social image), while nearly half of the respondents report positive aspects of Korean people as being compassionate, cooperative, good-natured and hard-working. As for reason for trusting Korean society, around a third report "because it is our country," followed by its future potential, and the good-nature and willingness of Korean people to work hard. The reasons for distrusting Korean society is the dishonesty politicians, corruption, institutional ineptness, and economic uncertainty. These results indicate a low level of collective efficacy in influencing and affecting change in Korean society.