This study aims to classify spatial living zones in remote island areas of Korea based on accessibility to basic services. Using QGIS-based network analysis and clustering methods, accessibility was measured at both local and regional levels for 321 inhabited islands with available, maritime transport data. Key services―healthcare, education, culture, commerce, and transportation― were used to derive accessibility indicators. Islands were categorized into four types: (1) Inland-connected Island Living Zones with easy land access, (2) Mid-distance individual Zones highly dependent on maritime transport, (3) Independent Island Living Zones with full internal service coverage, and (4) Remote Hub-Island-Connected Living Zones with core-periphery structures between central and surrounding islands. Each type exhibited distinct spatial and functional characteristics in terms of service dependency and geographic distribution. The findings highlight the need for differentiated strategies in service provision and spatial planning. This study provides empirical evidence to support customized policy development for improving quality of life in geographically isolated island regions.
This study analyzes the gap between the utilization and accessibility of agricultural and rural information among field practitioners engaged in agricultural infrastructure and rural development projects. A total of 91 information items were categorized into four domains―soil, drainage, farming, and farmland―and analyzed using the Importance-Performance Analysis (IPA) method combined with the Wilcoxon signed-rank test to ensure statistical robustness. The results show that practitioners in agricultural infrastructure projects generally have higher levels of information utilization but face greater barriers to access, particularly for soil (S2, S3, S6, S27), crop production (A17, A18, A22), and farmland (L9, L10, L14) data. Based on these findings, this study proposes four directions for improving the agricultural and rural information system: (1) building an integrated information framework reflecting user demand, (2) refining data disclosure standards to enhance accessibility while protecting privacy, (3) developing data-based planning guidelines and spatial decision-support tools, and (4) constructing a comprehensive data integration platform linking internal, external, and field data. Although the sample is limited to practitioners from the Korea Rural Community Corporation, the study offers practical insights for designing a user-oriented information system. Future research should expand to include local governments, research institutes, and private sectors to improve the policy applicability and inclusiveness of the system.
This study examines institutional challenges associated with Rural Specialization Districts (RSDs) established under the 2024 Rural Spatial Restructuring Act and proposes strategies to enhance their effectiveness for sustainable rural development. Through a theoretical review of rural spatial planning following the Act’s implementation, the research establishes its distinct scope. It further analyzes legal frameworks governing land use and zoning relevant to RSDs under other national laws, complemented by case studies from Japan and Germany. Based on these insights, the study identifies key policy tasks, including the development of detailed designation criteria for each RSD type, the management of RSD-related information systems, and the formulation of project plans tailored to district characteristics. Additionally, it proposes operational strategies aligned with three legal contexts: the National Land Planning Act, the Framework Act on Land Use Regulation, and the Rural Spatial Restructuring Act. Acknowledging the limitation that local governments are still in the early stages of planning, the study emphasizes the importance of institutional and strategic preparedness. Future institutional and policy refinements should be a continuous process, informed by practical experience gained from empirical evaluations and citizen participation once local governments have established their master and implementation plans.
The Agricultural Environment Conservation Program, implemented by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) since 2018, is a region-based environmental initiative aimed at reducing the environmental burden of agricultural activities through the promotion of eco-friendly farming practices, reduction of pesticide and fertilizer use, and protection of soil and water resources. The program encompasses the entire process from planning to implementation and evaluation, with participation from both individual farmers and community units. To ensure policy effectiveness, the establishment of a scientific and quantitative performance management system is essential. This study developed an integrated system for the Agricultural Environment Conservation Program, featuring automated implementation monitoring, spatial data analysis, and automated report generation. The system adopts a client-server architecture and incorporates advanced ICT technologies such as customized UI/UX, external API-based data collection, relational database storage, GeoJSON-based spatial visualization, and role-based access control. It systematically manages data on unit costs, budgets, activities, and land parcels, and improves monitoring efficiency through automated comparison between plans and actual performance, along with alert functions for incomplete or missing activities. Moreover, the system enables time-series analysis and environmental change prediction by linking satellite data, and supports administrative efficiency with pre-defined templates for automated report generation. The proposed system provides a foundation for quantitative performance management, systematic implementation oversight, and automation of field operations, and is expected to enhance the execution of agricultural environmental policies and contribute to the realization of a sustainable agricultural environment.
In this study, a survey was conducted targeting potential users demanders of residential farm to analyze the factors influencing the size of residential housing and vegetable garden within such farms. The main findings can be summarized as follows: First, the factor analysis revealed that utility-related factors consist of surrounding amenities, surrounding landscape, facility management method, and facility size, while cost-related factors consist of rental fees, travel distance, and travel time. Second, regarding housing size, it was found that individuals tend to prefer larger-scale residential farm housing when utility factors are higher, when the age group is younger, and when the intended length of stay is longer. Third, with respect to vegetable garden size, individuals showed a preference for larger garden sizes when cost factors are lower, when the respondent is male, and when the length of stay is longer.
The value of rural areas has evolved over time in response to changing social demands and environmental contexts. Traditionally perceived as production-oriented spaces, rural areas have increasingly been recognized for their cultural and environmental values due to industrialization, urbanization, population decline, and the dissolution of traditional communities. This study analyzes the shifts in rural discourse by examining representative rural development policy guidelines using text mining techniques. Three major policies were analyzed: the Saemaul Undong (1970s), the Rural Settlement Development Project (1990s), and the Comprehensive Rural Village Development Project (2010s). The analysis incorporated noun-based frequency analysis, social network analysis, and topic modeling. The results showed that the term “village” remained central throughout all periods, highlighting the enduring village-oriented focus of rural policy. Since the 1990s, the growing prominence of the term “planning” indicates a stronger emphasis on preparatory processes before project execution. In the 2010s, increased attention to “residents” reflected a shift toward participatory, bottom-up policy approaches. Earlier policies were centered on specific project components, while recent ones emphasize planning and implementation processes. Overall, the basic framework of rural policy has remained consistent, yet the growing importance of “planning” and “residents” reveals a gradual shift in focus. This study contributes by applying text mining techniques to rural policy documents, though its ability to fully capture the broader evolution of rural discourse remains limited. Future research should incorporate a wider range of discourse analysis methods to trace the ongoing transformation of rural values.
This study utilized the Topographic Position Index (TPI) to quantitatively identify the spatial characteristics of ruralness in Gochang County, Jeollabuk-do, and proposed management strategies for different landscape types. In response to the implementation of rural space restructuring policies, this study aimed to complement the limitations of existing urban planning-centered approaches and move beyond amenity-based resource classification by attempting a landscape interpretation that reflects topography, water systems, and spatial structure. Using 30-m SRTM DEM data, we calculated TPI for circular neighborhoods with a 500-m radius, representing the basic living-area unit. Hilly areas were then delineated where the slope was ≤ 10° and TPI was ≥ 5. After correlation analysis and standardization (Z-score), K-means clustering analysis (K=3) was conducted to classify Gochang's hilly areas into forest-type, facility farmland-type, and grassland-type. The forest type has high elevation, slope, and forest coverage, making it highly valuable for conservation. The facility farmland type is characterized by low elevation and flat terrain supporting intensive agricultural activities. The grassland type has a mixed structure with no dominant land use, offering high potential for land use conversion. Differentiated management strategies, such as ecological conservation, agricultural environment management, and mixed-use development, were proposed for each type. This study presents a practical analytical framework for spatializing rural characteristics based on topography, demonstrating its potential as foundational data for region-specific rural spatial planning.
The Agri-Environmental Conservation Program (AECP) is the most comprehensive agri-environmental payment scheme in Korea, encompassing a wide range of activities. Unlike existing direct payment schemes, the AECP operates through collective participation at the village level to enhance farmers’ engagement and the effectiveness of their practices. Accordingly, the program is expected to play a significant role in shaping the design and implementation of future direct payment schemes, depending on its performance and long-term sustainability. However, an assessment of the environmental performance of villages that initiated the program in 2019 revealed the need for institutional improvements to strengthen its policy effectiveness. The objective of this study is to propose policy measures to enhance the effectiveness of the AECP through a comprehensive evaluation of its current implementation. To this end, policy scenarios for the AECP were developed with reference to previous literature on agri-environmental payment schemes. In addition, an integer programming model was constructed to analyze these scenarios, drawing on research related to conservation planning. The scenario analysis demonstrated that an optimization approach based on environmental benefits and costs substantially improves both the cost and environmental effectiveness of individual activities. Furthermore, relaxing the per-capita subsidy limit for individual activities―rather than simply increasing the total budget―was found to be more effective in enhancing the program's cost efficiency. Finally, tightening the constraints on mandatory activities did not yield further improvements in environmental benefits or cost effectiveness compared with the optimization scenario. These findings underscore the need for institutional reforms that prioritize policy improvements grounded in evidence on environmental benefits and costs.
Recent climate change, extreme weather events, and global supply chain disruptions have intensified price volatility in the international grain market and heightened uncertainty in food security. For South Korea, with its low grain self-sufficiency rate, such external shocks can directly lead to food security instability. This underscores the urgent need for a systematic information system capable of providing timely assessments of crop conditions in major grain-producing countries and integrating this information into policy decision-making. This study aims to develop a system design framework tailored to Korea's circumstances by analyzing and comparing existing satellite-based crop monitoring systems in operation abroad, namely: Crop Explorer, Monitoring Agricultural ResourceS (MARS), the Global Information and Early Warning System (GIEWS), and CropWatch. The analysis showed that all four systems share the common feature of integrating satellite-derived vegetation indices with meteorological data to assess crop conditions and yields. At the same time, their variations in scope, objectives, and delivery methods illustrate how system designs are adapted to specific regional and policy needs. These differences provide practical insights for developing a framework suited to Korea's agricultural context and policy priorities. The Crop Explorer provides an open platform that integrates satellite and meteorological data with periodic updates. The MARS combines vegetation indices with crop growth models to deliver precision yield forecasts designed to support EU agricultural policies. The GIEWS emphasizes early warning of food crises through the Agricultural Stress Index (ASI), whereas CropWatch employs multi-layered spatial analysis and automated data processing to monitor crop conditions both in China and globally. Based on these findings, this study proposes a system design for Korea centered on five core components: (1) constructing high-resolution cropland maps using deep learning techniques, (2) employing advanced vegetation indices that capture crop physiological processes, (3) integrating reanalyzed meteorological datasets, (4) establishing automated large-scale data processing pipelines, and (5) providing a user-friendly web-based visualization platform. The proposed design is expected to serve as an evidence-based decision-support tool, enhancing the accuracy1) and timeliness of crop yield information, and thereby contributing to food supply-demand policies, disaster response, and the formulation of mid- to long-term agricultural strategies.
This study examines the developmental trajectory of Korea's agricultural Official Development Assistance (ODA) by comparing the agricultural aid Korea received from the United States (1945-1980) with Korea's agricultural ODA to four Southeast Asian countries―Laos, Vietnam, Cambodia, and Myanmar―between 2010 and 2024. To analyze the structural evolution of agricultural development, the study introduces a three-stage analytical framework consisting of Foundation- Performance-Self-Reliance. This framework reflects the sequential process observed in Korea's own agricultural modernization and provides a structured lens for assessing the maturity of agricultural ODA portfolios. Using historical documents on U.S. agricultural aid to Korea and CRS-based statistical data for Korea's agricultural ODA, the study classifies projects into the three stages and compares their composition over time and across countries. The results show that Korea's agricultural ODA broadly mirrors the developmental pathway shaped by U.S. assistance: initial foundational support for institutional and human capacity building, followed by productivity-enhancing interventions, and, more recently, support for research, policy, and value-chain development aimed at self-reliance. At the same time, the relative weight of each stage differs by recipient country, reflecting variations in agricultural development levels and needs. These findings demonstrate that Korea's agricultural ODA is not simply a sectoral intervention, but represents the transfer and reproduction of Korea's own historical development experience. The study contributes to the literature by proposing a structured, data-driven model for evaluating agricultural ODA and by suggesting policy implications for tailoring country-specific ODA strategies according to each recipient's position along the Foundation-Performance-Self-Reliance pathway.
The Public Direct Payment Scheme was introduced as a decoupled income support policy while enhancing the public functions of agriculture and rural areas. However, since its implementation, debates have persisted over its potential connection to production, probably resultign in oversupply of rice and falling prices. Empirical studies examining the actual effects of public direct payments on production remain limited. This study analyzes the impact of public direct payments on farmers’ agricultural production activities by applying a regression discontinuity design (RDD), using the off-farm income threshold (KRW 37 million) as the cutoff criterion. The analysis employs five years of raw data from the Farm Household Economy Survey (2018-2022), dividing the sample into two pre-implementation years and three post-implementation years. Land area and labor hours, the key production factors, were set as dependent variables in our RDD experiments. The empirical results reveal that, after the scheme's introduction, beneficiary households experienced greater reductions in rented land area and hired labor hours compared to non-beneficiaries. These findings suggest that public direct payments may function as transfer income substituting for farm income, thereby partially reducing incentives to invest in production inputs. However, the magnitude of these effects is minimal, yielding results that are more consistent with the view that the scheme is production-neutral and largely decoupled from farm production decisions. By empirically examining the linkage between the scheme and production using the off-farm income threshold as the cutoff, this study provides a useful foundation for future reforms and policy evaluation of direct payment schemes in agriculture.
This study proposes extending a central-place hierarchy analysis based on the Davies functional index beyond a single county to adjacent counties to enhance the effectiveness of Basic Plans under the “Act on the Reorganization and Regeneration of Rural Space.” The case area is Gochang-gun and its border towns in Yeonggwang, Jangseong, Buan, and Jeongeup. Using 42 SOC functions from the Rural Spatial Information System, facilities were deduplicated and aggregated at the legal-ri (eup/myeon seat) level; sectoral totals were rescaled to 100 to obtain location coefficients, from which functional indices and centrality shares were computed. Analyzing only Gochang showed centrality concentrated in Gochang-eup; including adjacent towns pushed several myeon to lower tiers, indicating that peripheral areas may rely on centers in neighboring counties rather than Gochang-eup. A risk of overvaluation was observed for sports and rest facilities due to rarity, implying potential metric distortion relative to core public functions such as hospitals and emergency services. Accordingly, the Basic Plan should incorporate: first, routine, lifestyle-area analyses that include neighboring counties; second, clear criteria for defining central-place boundaries and weights reflecting facility scale and functional importance; third, standardized SOC inclusion/exclusion lists; and fourth, travel time and access modes. As limitations, we note our reliance on public data and the failure to consider population size, mobility patterns, and facility capacities; going forward, we propose methods that explicitly incorporate these factors.
Since the launch of the second Trump administration, the United States has been imposing high reciprocal tariffs on countries around the world. In response to the US tariff policy, South Korea is considering joining the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) as part of its trade diversification efforts, and China has also continued its pursuit of CPTPP membership since 2021. This study examined the impact of tariff elimination of Chinese kimchi imports on the Korean Chinese cabbage market from 2026 to 2035 using a dynamic partial equilibrium model, assuming that Korea and China join the CPTPP in 2026. According to the scenario analysis result, if tariffs on Chinese kimchi were eliminated immediately since 2026, Chinese cabbage imports would increase by an average of approximately 3% compared to the baseline over the forecast period. The increase in imports is expected to reduce cultivated area and production by up to 0.8%, and agricultural production value by up to 1.8% compared to the baseline. The results of this study would serve as useful information for policymakers and market participants in the Chinese cabbage and kimchi industries in future CPTPP or other trade agreements with China.
An Analysis of the Physiological Changes and Usability Evaluation of Virtual Reality-Based Therapeutic Programs by User Type - HRV, SSQ and Usability Test -
구희동 Koo Hee-dong , 신민주 Shin Min-ju , 이왕록 Lee Wang-rok , 정순진 Jeong Sun-jin , 조예슬 Jo Ye-seul , 김대식 Kim Dae-sik
This study evaluated Heart Rate Variability(HRV), the Simulator Sickness Questionnaire(SSQ), and the Usability Test(UT) f or the virtual reality-based therapeutic program, Cheer UVR, i n the general population, elderly, and individuals with disabilities. The assessment used Oculus Quest 2 and the CheerU VR program. Participants included general(N=21), elderly(N=68), and individuals with disabilities(N=50). Evaluations of HRV, SSQ, and UT were conducted before, during, after the VR experience. Statistical analyses were performed using ANOVA and Chi-squared tests using SPSS. Analysis of HRV changes indicated that the general population exhibited greater change in mean heart rate than the other groups, suggesting a stronger autonomic nervous system response. The elderly and individuals with disabilities demonstrated sympathetic dominance even after the experience compared to the general population, indicating potential vulnerability to tension, energy consumption, and stress. Regarding SDNN and RMSSD, the general population showed statistically significant improvement in SDNN and RMSSD; the elderly showed no significant changes, while individuals with disabilities showed limited improvement. Statistically significant differences(p<.05) were observed for HR Mean in the general population, HR Min and HR Mean in the elderly, and HF and SDNN in individuals with disabilities. For the SSQ, statistically significant differences in nausea symptoms by participant group(p=.048), with post-hoc analysis revealing that individuals with disabilities reported higher symptom levels than the general population. In the UT, questions regarding the program’s effects on socially vulnerable groups received positive responses across all groups. Psychological health promotion was identified as the primary expected outcome, which was statistically significant(p=.042). Additionally, all groups indicated that such a VR program would encourage visits to actual healing farms; this response was also significant(p=.027). Evaluating user satisfaction, design validity, and field applicability, only the question on device operation convenience was statistically significant(p=.001). In conclusion, this study suggests that virtual reality technology can function as an intervention tool to enhance physiological and psychological health, provides foundational evidence for the development of similar VR-based therapeutic programs.
This study presents a quantitative framework for integrating Farm Map-based farmland change analysis into rural spatial planning under the Act on Rural Spatial Restructuring and Regeneration(2023). Using Farm Map datasets from 2017 and 2024 for Yangsan City, South Korea, the research identifies land-use transitions through change detection and spatial hotspot analysis to diagnose development pressures in peri-urban rural areas undergoing rapid land conversion. The results show that total farmland area declined by approximately 16.7%, primarily due to the conversion of paddy and dry fields into non-agricultural uses. Hotspot analysis using the Getis-Ord Gi* statistic revealed statistically significant clusters of farmland loss concentrated in southern Mulgeum-eup, southwestern Dong-myeon, and along major transport corridors in Sangbuk-myeon and Habuk-myeon. These clusters correspond to zones of intensified metropolitan expansion. In contrast, farmland restoration occurred sporadically, suggesting a lack of systematic policy intervention. The findings demonstrate the value of Farm Map data in detecting fine-scale spatial changes and identifying priority zones for managing uncontrolled development. The proposed analytical framework offers empirical evidence to support zoning and land-use management within rural spatial planning. Future research should extend this approach to multiple regions, integrate socioeconomic and environmental variables, and develop automated hotspot-based decision-support tools. Overall, Farm Map-based spatial diagnostics strengthen the scientific foundation of rural spatial planning, contributing to sustainable land use and the preservation of rurality.
Development and Application of a Nexus-based Impact Assessment Framework for Agricultural Cultivation Activities in the Agricultural Environment Conservation Program
윤푸른 Yoon Pu Reun , 김마가 Kim Maga , 최진용 Choi Jin-yong
This study developed a nexus-based impact assessment framework to quantitatively evaluate the interrelationships among water, energy, food, carbon, and water quality (W-E-F-C-WQ) in major agricultural activities under the Agricultural Environment Conservation Program (AECP). While agricultural intensification has improved productivity, it has also increased environmental burdens such as greenhouse gas emissions and nutrient pollution. To address these challenges, an integrated data- modeling-nexus linkage system was established based on the APEX and APEX-Paddy models, incorporating climate, soil, crop, and management datasets. Using both model simulations and quantitative coefficients, this system estimated crop yield, water use, energy consumption, carbon emissions, and nutrient loads across different agricultural management practices. The results were standardized as relative change rates from reference activities, and an integrated nexus impact index was calculated using a radar-type approach integrating five nexus elements. The framework enables quantitative comparison of trade-offs and synergies among agricultural activities, supports the derivation of optimal agricultural management scenarios, and can be applied to village-level planning and evaluation within the AECP. It also allows region-specific weighting of nexus elements to reflect local priorities and policy objectives. The current framework focuses on crops with available datasets but can be further advanced by obtained crop parameters, improving validation with field measured data, and linking additional quantitative modules for non-modeling practices. This study establishes a practical and scalable decision-support framework for sustainable agricultural resource management and environmental policy planning in response to climate change.
This study developed the Agricultural Environment Impact Assessment System to quantitatively evaluate the environmental outcomes of the Agricultural Environment Conservation Program (AECP), implemented by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) since 2019. Existing evaluation methods―primarily based on awareness surveys or individual indicators―have been limited in assessing the program’s overall environmental effects. To address this gap, this study established an assessment framework that measures environmental changes resulting from conservation activities by analyzing interactions among key agricultural environment resources (water, soil, water quality, energy, carbon, and ecology). The framework quantifies differences between baseline practices and conservation activities by calculating core indicators using the APEX/ APEX-paddy model and country-specific coefficients. These indicators are then integrated into a single comprehensive evaluation index using AHP/ANP-based weighting, and their economic value is monetized using the opportunity cost approach. The Impact Assessment System was implemented as a web and mobile based platform and linked with a separately developed the Implementation Monitoring System, enabling automated real-time evaluation from data collection to outcome analysis. The system developed in this study enhances the efficiency and transparency of AECP operation by providing a scientifically grounded evaluation methodology. Furthermore, it has strong potential for application and expansion to national sustainable agriculture policies, such as the Public Benefit Direct Payment Program and climate-smart agriculture initiatives.
This study aimed to improve the community sector evaluation system and reset the validity and weighting of criteria. The selection of target villages is a critical process that determines the success or failure of program implementation. However, there are currently many complex procedures and overlapping selection criteria at each stage. Existing evaluation criteria were reviewed and duplicates removed, restructuring the system into three sector―community capacity, local government capacity, and sustainability―with 12 detailed indicators. Two online surveys assessed criteria validity and the weighting of each evaluation criteria using the Analytic Hierarchy Process(AHP) technique. The importance analysis of each evaluation criteria showed that items related to community capacity, such as resident participation rate, plan participation and capacity-building efforts, were generally considered the most important. This study can contribute to enhancing the effectiveness and feasibility of the Agricultural Environment Conservation Program by strengthening the community-centered evaluation system and establishing selection criteria based on resident participation and community capacity. It can also help restore rural community functions and ensure the sustainability of environmental conservation activities.
