• Title/Summary/Keyword: 글로벌 기후 데이터

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Study on Developing the Information System for ESG Disclosure Management (ESG 정보공시 관리를 위한 정보시스템 개발에 관한 연구)

  • Kim, Seung-wook
    • Journal of Venture Innovation
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    • v.7 no.1
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    • pp.77-90
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    • 2024
  • While discussions on ESG are actively taking place in Europe and other countries, the number of countries pushing for mandatory ESG information disclosure related to non-financial information of listed companies is rapidly increasing. However, as companies respond to mandatory global ESG information disclosure, problems are emerging such as the stringent requirements of global ESG disclosure standards, the complexity of data management, and a lack of understanding and preparation of the ESG system itself. In addition, it requires a reasonable analysis of how business management opportunities and risk factors due to climate change affect the company's financial impact, so it is expected to be quite difficult to analyze the results that meet the disclosure standards. In order to perform tasks such as ESG management activities and information disclosure, data of various types and sources is required and management through an information system is necessary to measure this transparently, collect it without error, and manage it without omission. Therefore, in this study, we designed an ESG data integrated management model to integrate and manage various related indicators and data in order to transparently and efficiently convey the company's ESG activities to various stakeholders through ESG information disclosure. A framework for implementing an information system to handle management was developed. These research results can help companies facing difficulties in ESG disclosure at a practical level to efficiently manage ESG information disclosure. In addition, the presentation of an integrated data management model through analysis of the ESG disclosure work process and the development of an information system to support ESG information disclosure were significant in the academic aspects needed to study ESG in the future.

Establishment of hydraulic/hydrological models in the Mekong pilot area using global satellite-based water resources data (focusing on HEC-RTS/HMS model application) (글로벌 위성기반 수자원 데이터 활용 메콩지역 수리/수문모델 시범 구축 (HEC-RTS/HMS 모형 적용을 중심으로))

  • Cho, Younghyun;Park, Sang Young;Park, Jin Hyeog
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.111-111
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    • 2021
  • 메콩지역은 최근 연 7%에 육박하는 경제성장률을 달성하며 아세안의 고성장을 지속 견인하고 있으나, 기후변화 및 급속한 도시화로 매년 가뭄·홍수 등 물 관련 재해 발생 빈도 및 강도 증가와 이에 따른 상·하류 국가간 물 분쟁 등으로 인해 메콩지역 지속가능 발전에 지장이 초래되고 있다. 이에 한국과 미국은 메콩우호국(Friends of the Lower Mekong, FLM) "메콩지역 수자원 데이터 관리 및 정보공유 강화에 관한 공동성명(2018년 8월)"을 계기로 메콩유역의 실시간 수자원 변동 모니터링 및 분석과 수자원 데이터 공동활용 역량을 강화하여 효율적이고 과학적인 수자원관리 지원과 함께 한국의 신남방정책과 미국의 인도-태평양 전략 시너지효과를 극대화하고자 메콩 주변국 재해경감 및 수자원 데이터 활용 역량강화를 위한 글로벌 위성기반 수문자료의 생산·활용 및 홍수·가뭄 등의 수재해 분석기술을 개발하고 있다. 여기에는 한국 K-water의 물관리 기술과 미국 NASA, USACE의 위성활용 및 수자원분석 기술을 접목하여 메콩지역의 체계적인 물관리 및 재해로부터 안전성 확보 기여에 목표를 두고 연구를 진행 중에 있다. 본 연구에서는 전 세계적으로 광범위하게 활용되고 있는 미공병단(USACE, U.S. Army Corps of Engineers)의 HEC software 프로그램을 메콩 시범지역(pilot area)에 적용하여 수리/수문모델 구축을 진행코자 한다. 구축되는 모형은 유역 상류 댐의 연계 모의운영 및 하류 홍수분석이 동시 가능한 HEC-RTS(Real-Time Simulation)로 이는 HEC-HMS, -ResSim, -RAS와 -FIA 모형이 순차적으로 결합된 수리/수문 모델링 시스템이다. 모형의 시범적용 지역은 현지 메콩위원회(MRC, Mekong River Comission)의 의견 등을 반영, 메콩강 하류지역(Lower Mekong) 본류 유역에 위성 자료 활용 및 준실시간(near real-time)으로 댐 모의운영 등을 고려할 수 있는 JingHong댐(중국 란창강 최하류)에서 라오스 Xayaburi댐(메콩강 최상류)까지의 구간을 선정하였다. 한편, 금번 연구에서는 HEC-RTS 중 HMS 모형 적용을 중심으로 가용한 위성자료(GPM IMERG)와 K-LIS 지표 모형 생산 자료를 활용하여 과거 홍수사상에 대한 모의를 고려하였다. 아울러, 연구에서 구축된 HMS 모형은 HEC-RTS에 포함되어 메콩 시범지역의 종합적 수리/수문분석에 적용될 예정이다.

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Global Value Chain Integration in the Korean Strawberry Industry: Focusing on Farmers in Jinju (한국 딸기산업의 글로벌 가치사슬 통합 과정: 진주시 농업인을 중심으로)

  • Sohyun Park
    • Journal of the Economic Geographical Society of Korea
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    • v.26 no.3
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    • pp.274-288
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    • 2023
  • While the integration into global value chains has garnered attention as a rural development strategy, less is known about why some integrations are successful while others are not. This study draws on rent theory and on empirical examples from Jinju and Nonsan, the two biggest strawberry production regions in South Korea, to explore the mechanisms of Jinju creating and exclusively retaining monopoly rents from the exports. Based on five months of fieldwork and in-depth interviews with stakeholders, the findings show that a producer-driven chain integration into the overseas markets was possible in Jinju due to the natural barriers to entry based on an exportable variety, as well as the region's climate conditions being suitable to the variety. Moreover, the farmers have attempted to retain the monopoly rents and extra profits from public supports by associating producers. The horizontally associated farmers stabilized their positions by enhancing their bargaining power against exporters, as well as by managing access to the public supports by controlling memberships.

Detecting Weak Signals for Carbon Neutrality Technology using Text Mining of Web News (탄소중립 기술의 미래신호 탐색연구: 국내 뉴스 기사 텍스트데이터를 중심으로)

  • Jisong Jeong;Seungkook Roh
    • Journal of Industrial Convergence
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    • v.21 no.5
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    • pp.1-13
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    • 2023
  • Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

International Case Study and Strategy Proposal for IUCN Red List of Ecosystem(RLE) Assessment in South Korea (국내 IUCN Red List of Ecosystem(생태계 적색목록) 평가를 위한 국제 사례 연구와 전략 제시)

  • Sang-Hak Han;Sung-Ryong Kang
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.408-416
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    • 2023
  • The IUCN Red List of Ecosystems serves as a global standard for assessing and identifying ecosystems at high risk of biodiversity loss, providing scientific evidence necessary for effective ecosystem management and conservation policy formulation. The IUCN Red List of Ecosystems has been designated as a key indicator (A.1) for Goal A of the Kunming-Montreal Global Biodiversity Framework. The assessment of the Red List of Ecosystems discerns signs of ecosystem collapse through specific criteria: reduction in distribution (Criterion A), restricted distribution (Criterion B), environmental degradation (Criterion C), changes in biological interaction (Criterion D), and quantitative estimation of the risk of ecosystem collapse (Criterion E). Since 2014, the IUCN Red List of Ecosystems has been evaluated in over 110 countries, with more than 80% of the assessments conducted in terrestrial and inland water ecosystems, among which tropical and subtropical forests are distributed ecosystems under threat. The assessment criteria are concentrated on spatial signs (Criteria A and B), accounting for 68.8%. There are three main considerations for applying the Red List of Ecosystems assessment domestically: First, it is necessary to compile applicable terrestrial ecosystem types within the country. Second, it must be determined whether the spatial sign assessment among the Red List of Ecosystems categories can be applied to the various small-scale ecosystems found domestically. Lastly, the collection of usable time series data (50 years) for assessment must be considered. Based on these considerations, applying the IUCN Red List of Ecosystems assessment domestically would enable an accurate understanding of the current state of the country's unique ecosystem types, contributing to global efforts in ecosystem conservation and restoration.

A Study on Distributed Collective Energy Policy Changes: Focusing on the National Heat Map Project Based on Energy Data (분산형 집단에너지 정책변동 연구: 에너지 데이터 기반의 국가 열지도 사업을 중심으로)

  • Park Eunsook;Park Yongsung
    • Knowledge Management Research
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    • v.24 no.1
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    • pp.195-221
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    • 2023
  • As the global energy and climate crisis has complicated interests of each country, the agenda that requires a global response has recently been revived. In particular, Korea is highly dependent on energy imports and continues to have high energy consumption, low efficiency of energy consumption, and high greenhouse gas emissions, so innovative and effective energy policies are urgently needed to achieve energy efficiency and carbon neutrality. In this study, among the changes in distributed district energy policy after the integrated energy method was introduced in Korea in the mid-1980's, the case of the "National Heat Map Project" policy implementation is analyzed with a modified multi-flow model. The 10 years of the Lee Myung-bak and Park Geun-hye administrations, the period of study, was a period in which the main paradigm of energy policy shifted to a "distributed energy platform" and policy transitions such as policy agenda setting, policy drift, and policy revision were made. A study on the process would be meaningful.

Study on Energy Efficiency Improvement in Manufacturing Core Processes through Energy Process Innovation (에너지 프로세스 혁신을 통한 제조 핵심 공정의 에너지 효율화 방안 연구)

  • Sang-Joon Cho;Hyun-Mu Lee;Jin-Soo Lee
    • Journal of Advanced Technology Convergence
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    • v.2 no.4
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    • pp.43-48
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    • 2023
  • Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

A Bibliometric Study on Sustainable Development Goals (SDGs) Research Trends in Entrepreneurship (키워드 네트워크 분석을 활용한 창업분야 지속가능발전목표(SDGs) 연구동향 분석)

  • An, Seung Kwon;Choi, Min Jung
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.2
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    • pp.21-34
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    • 2023
  • The purpose of this study is to examine the extent of Sustainable Development Goals (SDGs)-related research in the field of entrepreneurship globally since the adoption of the SDGs at the UN General Assembly, and to compare international and domestic research trends in order to determine the direction of SDGs-related research in entrepreneurship in Korea. Utilizing three databases-Web of Science (WoS), KCI, and DBpia- SDGs-related studies in entrepreneurship were extracted by employing specific search terms. After data purification, a total of 356 studies abroad and 4 studies in Korea were used for analysis. After data purification, a total of 356 international studies and 4 Korean studies were analyzed. Due to the limited number of domestic studies, the research trends were examined by conducting frequency analysis and keyword network analysis on international studies alone. Frequency analysis revealed that SDGs research in entrepreneurship primarily focused on sustainability-related terms and was conducted in conjunction with business models, innovation, entrepreneurship education, and strategies. Furthermore, yearly frequency analysis demonstrated an expansion of topics to encompass research on entrepreneurship and SDGs policies, the roles and capabilities of female entrepreneurs in SDGs implementation, energy start-ups and SDGs, directions for implementing SDGs in business schools and SDGs education, indicators for SDGs implementation and evaluation, and technologies for sustainability. The keyword network analysis identified central topics such as business, sustainability, SDGs, innovation, entrepreneurship, business models, and education, with research areas extending to entrepreneurship ecosystems, change and strategy, ethics, and climate. This study holds significance in establishing a foundation for SDGs research in entrepreneurship, which is currently an underexplored area in Korea, by presenting emerging research trends related to SDGs in entrepreneurship.

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Comparative study of flood detection methodologies using Sentinel-1 satellite imagery (Sentinel-1 위성 영상을 활용한 침수 탐지 기법 방법론 비교 연구)

  • Lee, Sungwoo;Kim, Wanyub;Lee, Seulchan;Jeong, Hagyu;Park, Jongsoo;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.57 no.3
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    • pp.181-193
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    • 2024
  • The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.