• Journal of Appropriate Technology
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• v.7 no.2
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• pp.162-171
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• 2021

The Korean government proposed the K-SDGs in 2019 to promote the UN SDGs, but the role and tasks of science and technology, an important means of implementing the SDGs, have not been materialized. Accordingly, the role of science and technology ODA for the SDGs was established through the Ministry of Science and ICT's policy research project 'Science and Technology ODA Promotion Roadmap for Spreading the New Southern Policy and Realizing the 2030 SDGs'. In addition, goals, strategies, and core tasks for the next 10 years were derived in 10 fields such as water, climate change, energy, and ICT. In this paper, we analyze 30 key tasks of the ODA promotion roadmap for science and technology for the realization of SDGs, and propose mid- and short-term tasks and implementation plans for effective roadmap promotion. Among the key tasks in each field, four common elements were derived: ICT/smartization, a global problem-solving center, cooperation/communication platform, and business model/startup support platform/living lab that can create and integrate roadmap implementation conditions. In addition, the four mid- and short-term tasks, 1) Establishment of science and technology ODA network, 2) Establishment of living lab business platform linked to start-up support business, 3) Local smartization of recipient countries, and 4) Expand and secure sustainability of global problem-solving centers, were set in relation to the implementation of the detailed roadmap. For the derived mid- and short-term tasks, detailed implementation plans based on the ICTization of global problem-solving centers were presented. The implementation of the mid- and short-term tasks presented in this paper can contribute to the more effective achievement of the science and technology ODA roadmap, and it is expected that Korea's implementation of SDGs will also achieve high performance.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.68-81
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• 2023

This study aims to establish a scenario based on the spacing and arrangement of the roadside trees to reduce heat waves and fine dust in cities that occurred during the urbanization process and to quantitatively analyze the degree of reduction. The ENVI-met 5.0.2v model, a micro-climate simulation program, was used to analyze the degree of improvement in the thermal environment and fine dust according to the roadside tree scenario. As a result of temperature analysis according to street tree spacing, the narrower the distance between roadside trees, the lower the temperature during the day as the number of planted trees increased, and a similar pattern was shown regardless of the distance between roadside trees in the morning and evening. In the case of fine dust emitted from the road, the concentration of fine dust increased slightly due to the increase in roadside trees, but the concentration of sidewalks where people walk increased slightly or there was no difference because of blocking fine dust on trees. The temperature according to the arrangement of street trees tended to decrease as the number of planted trees increased as the arrangement increased. However, not only the amount of trees but also the crown projected area was judged to have a significant impact on the temperature reduction because the temperature reduction was greater in the scenario of planting the same amount of trees and widening the interval of arrangement. In terms of the arrangement, the fine dust concentration showed a difference from the results according to the interval, suggesting that the fine dust concentration may change depending on the relationship between the main wind direction and the tree planting direction. By quantitatively analyzing the degree of thermal environment and fine dust improvement caused by roadside trees, this study is expected to promote policies and projects to improve the roadside environment efficiently, such as a basic plan for roadside trees and a project for wind corridor forests.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.71-82
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• 2023

Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO₂ absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO₂ concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.13-35
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• 2023

Ocean currents play the most important role in causing and controlling global climate change. The water depth of the Yellow Sea is very shallow compared to the East Sea, and the circulation and currents of seawater are quite complicated owing to the influence of various wind fields, ocean currents, and river discharge with low-salinity seawater. The Yellow Sea Warm Current (YSWC) is one of the most representative currents of the Yellow Sea in winter and is closely related to the weather of the southwest coast of the Korean Peninsula, so it needs to be treated as important in secondary-school textbooks. Based on the 2015 revised national educational curriculum, secondary-school science and earth science textbooks were analyzed for content related to the YSWC. In addition, a questionnaire survey of secondary-school science teachers was conducted to investigate their perceptions of the temporal variability of ocean currents. Most teachers appeared to have the incorrect knowledge that the YSWC moves north all year round to the west coast of the Korean Peninsula and is strong in the summer like a general warm current. The YSWC does not have strong seasonal variability in current strength, unlike the North Korean Cold Current (NKCC), but does not exist all year round and appears only in winter. These errors in teachers' subject knowledge had a background similar to why they had a misconception that the NKCC was strong in winter. Therefore, errors in textbook contents on the YSWC were analyzed and presented. In addition, to develop students' and teachers' data literacy, class materials on the YSWC that can be used in inquiry activities were developed. A graphical user interface (GUI) program that can visualize the sea surface temperature of the Yellow Sea was introduced, and a program displaying the spatial distribution of water temperature and salinity was developed using World Ocean Atlas (WOA) 2018 oceanic in-situ measurements of water temperature and salinity data and ocean numerical model reanalysis field data. This data visualization materials using oceanic data is expected to improve teachers' misunderstandings and serve as an opportunity to cultivate both students and teachers' ocean and data literacy.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• 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.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.71-86
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• 2024

Despite the increasing importance of urban parks' ecological functions in dealing with the climate crisis, ecological parks are not clearly defined in Korea's legal system. Numerous ecological parks created nationwide cannot be systematically designated and managed due to various legal bases and varying management authorities. It is important to clarify the legal status of ecological parks in order to lead the ecological paradigm shift of urban parks and to improve the natural park system for a comprehensive and integrated approach to protect the national ecosystem. To this end, related laws were analyzed to identify problems and to draw directions for legislative improvement. Through the literature review of relevant laws, acts, and ordinances, six major directions for improvement were suggested based on the analysis of problems. First, the legal status of ecological parks in the administrative dichotomy of the current park system is ambiguous, and ecological parks should be clarified through the revision of park-related laws. Second, an ecological park can be defined as a sustainable park created and managed in an ecological manner, promoting the protection and restoration of the ecosystem, conservation, and promotion of biodiversity, and balancing nature observation, ecological learning, and leisure activities. Third, the role of the state and local governments should be systematically revised to lead to a new park planning and management model through new governance. Fourth, since the characteristics of ecological parks are affected by individual laws, the possibility of overlapping ecological parks for other uses should be allowed. Fifth, detailed guidelines and standard ordinances need to be enacted to meet the goals, principles, and facilities of ecological parks. Lastly, along with the revision of the laws, ordinances by local governments also need to be more concrete. This study, which tracks various legal realities related to ecological parks, can contribute to policymaking that can systematize the foundation for the creation of ecological parks to preserve nationwide ecosystems and provide citizens with opportunities to experience and learn about nature.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.40-50
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• 2024

Pine forests are continuously declining due to competition with broadleaf trees, such as oaks, as a consequence of changes in the natural dynamics of forest ecosystem. This natural decline creates a risk of losing the various benefits pine trees have provided to people in the past. Therefore, it is necessary to prepare future forest management directions by considering the state of pine tree decline in each region. The goal of this study is to understand the characteristics of pine forest changes according to forest dynamics and to predict future regional changes. For this purpose, we evaluated the trend of change in pine forests and extracted various variables(topography, forest stand type, disturbance, and climate) that affect the change, using time-series National Forest Inventory (NFI) data. Also, using selected key variables, a model was developed to predict future changes in pine forests. As a results, it showed that the importance of pine trees in forests across the country has decreased overall over the past 10 years. Also, 75% of the sample points representing pine trees remained unchanged, while the remaining 25% had changed to mixed forests. It was found that these changes mainly occurred in areas with good moisture conditions or disturbance factors inside and outside the forest. In the next 10 years, approximately 14.2% of current pine forests was predicted to convert to mixed forests due to changes in natural forest dynamics. Regionally, the rate of pine forest change was highest in Jeju(42.8%) and Gyeonggi(26.9%) and lowest in Gyeongbuk(8.8%) and Gangwon(13.8%). It was predicted that pine forests would be at a high risk of decline in western areas of the Korean Peninsula, including Gyeonggi, Chungcheong, and Jeonnam. This results can be used to make a management plan for pine forests throughout the country.