• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.73-81
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• 2023

To understand salinity status of fresh water and paddy soils and the susceptibility of rice to salinity stress of Gunnae reclaimed tidelands, salinity monitoring was conducted in rainy and dry seasons. For fresh water, a high salinity was observed at the sampling location near the sluice gate and decreased with distance from the gate. This spatial pattern of fresh water salinity indicates the necessity of spatial distribution of salinity in the assessment of salinity status of fresh water. Interestingly, there was significant correlation between rainfall amount and salinity, implying that salinity of fresh water varies with rainfall and thus it may be possible to predict salinity of water using rainfall. Soil salinity also higher near the gate, reflecting the influence of high saline water. In addition, the groundwater salinity also high to threat rice growth. Though soil salinity status indicated low possibility of sodium injury, there was changes in soil salinity status during the course of rice growth, suggesting that more intensive monitoring of soil salinity may be necessary for soil salinity assessment. Our study suggests the necessity of intensive salinity monitoring to understand the spatio-temporal variations of salinity of water and soil of reclaimed tideland areas.

• Journal of Bio-Environment Control
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• v.25 no.1
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• pp.30-41
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• 2016

Korean government has planned to increase the productivity of horticultural crops and to expand supply smart greenhouse for energy saving by modernization of horticultural facilities based on ICT in policy. However, the diversity and linkages of monitoring and control are significantly insufficient in the agricultural sector in the current situation. Therefore, development of a service system with smart-farm based on the internet of things(IoT) for intelligent systemization of all the process of agricultural production through remote control using complex algorithm for diverse monitoring and control is required. In this study, domestic and international research trend related to ICT-based horticultural facilities was briefly introduced and limits were analyzed in the domestic application of the advanced technology. Finally, future core technologies feasible to graft in agricultural field were reviewed.

• Journal of Korean Society of Rural Planning
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• v.26 no.2
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• pp.117-126
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• 2020

In this study, demands of smart technology development were analyzed for rural village communities. Questionnaire items were derived by grasping the current status of information and communication technology. 49 villages in 8 regions were selected and surveys and statistical analysis were conducted. The main results of the study are as follows. First, 92% of community leaders use smartphones, search for information (38%), communicate with the Internet (36%) using smartphones, use KakaoTalk (31%), and Facebook (24%). Second, in the rural and urban exchange activities, promote support information service (51%) and promote method suggestion service (48.5%) showed that the demand for services in promote field was high. It is linked to the creation of economic opportunities. Third, in the income and production activities, demand for distribution services technology (39.3%) was high in the field of production and distribution, and cold chains that help maintain freshness until food, such as meat, fish, and vegetables are delivered to consumers when agricultural products are distributed. The constant temperature control system needs to be actively introduced. Fourth, autonomy activities showed the highest demand for air conditioning and control systems (34.2%) of community building, and the lowest demand for electronic voting (9.4%) and videoconferencing (9.4%) services. Lastly, in the general activity area of the community, the demand for technology of emergency services (37.1%) and health self-diagnosis service (35.4%), which are technologies in the welfare sector, ranked first and second respectively.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.127-138
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• 2022

In responding to climate change in the agricultural sector, Climate Smart Agriculture (CSA) is an approach to establish a sustainable agricultural system through comprehensive management of technology, policy, and investment. The international community is continually expanding CSA implementation, and it became more important to understand the status of the domestic agriculture system and practices that are relevant to CSA. This study explored the available CSA in domestic agricultural systems and presented the order of relative importance of CSA technology. AHP analysis is employed for the evaluation with the following criteria: productivity, marketability, adaptability, and mitigation. The relative importance is evaluated with six agricultural technologies (soil, crop management, water, energy efficiency, alternative energy, and precision agriculture) in 28 agricultural technology sectors. The results of the AHP analysis showed that 'alternative energy' was found to be a top priority among the agricultural technology sectors, and 'shallow depth drain in rice paddy' was a top priority for agricultural technology. Also, the 'marketability' in soil and water sectors, 'mitigation' in crop management, and 'adaptability' in energy efficiency and alternative energy were given higher priority. The results of this study can be used as a good source for strategic CSA preparation and application.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.2
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• pp.29-36
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• 2022

This study analyzed the effects of building and greenhouse structural code on the structural design and the greenhouse construction cost. The over-design possibility of greenhouse was analyzed when building structural code was applied using standard smart greenhouse drawings. The possibility of decrease in greenhouse construction cost was investigated if the currently applied building structural code was replaced with greenhouse structural code. As a result of comparing the member sizes with the standard drawings, building structural code was designed with 13%~74% more steel than greenhouse structural code. When building construction estimate was replaced with greenhouse construction estimate, it was possible to reduce the total construction cost of the glass greenhouse by 17% and that of the vinyl greenhouse by 14%. Since there is no standard construction estimate suitable for greenhouses, the wage unit price is set excessively, and the construction cost of the smart greenhouse is increasing. In conclusion, it is necessary to establish greenhouse structural code and greenhouse construction estimate to lower the greenhouse construction cost.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.743-752
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• 2020

The purpose of this study was to estimate the economic evaluation of a smart farm investment for tomatoes and strawberries. In addition, the potential adoption rate of the smart farm was derived for different scenarios. This study analyzed the economic evaluation with the net present value (NPV) method and estimated the adoption potential of the smart farm with the trade-off analysis, minimum data (TOA-MD) model. The results were as follows: The analysis of the net present value shows that the smart farm investment for the two crops are economically feasible, and the minimum prices for the tomatoes and strawberries should be 1,179 and 3,797 won/kg to secure a sufficient economic feasibility for the smart farm investment. Next, the analysis of the potential adoption rates for smart farms through the TOA-MD model showed that when the support ratio for the adoption of a smart farm system was 50% and the price increase rates were, respectively, - 5, 2.5, 0, 2.5, and 5%, the conversion rates for tomato farms to switch to smart farms were 0.97, 1.78, 3.05, 4.91, and 7.47%, while the ratios of the strawberry farms to switch to smart farms were 0.12, 0.29, 0.65, 1.33, and 2.53%, respectively. This study has some known limitations, but it provides useful information on decision making about smart farm adoption and can contribute to government policies on smart farms.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.51-63
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• 2022

Up-to-date statistics of crop cultivation status is essential for farm land management planning and the advancement in remote sensing technology allows for rapid update of farming information. The objective of this study was to develop a classification model of rice paddy or winter crop fields based on NDWI, NDVI, and HSV indices using Sentinel-2 satellite images. The 18 locations in central Korea were selected as target areas and photographed once for each during summer and winter with a eBee drone to identify ground truth crop cultivation. The NDWI was used to classify summer paddy fields, while the NDVI and HSV were used and compared in identification of winter crop cultivation areas. The summer paddy field classification with the criteria of -0.195

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.45-56
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• 2024

Faced with aging populations, declining resources, and limited agricultural productivity, rural areas in South Korea require innovative solutions. This study investigated the potential of drone-based vegetation indices (VIs) to analyze soybean growth patterns in open-field smart agriculture in Goesan-gun, Chungbuk Province, South Korea. We monitored multi-seasonal normalized difference vegetation index (NDVI) and the normalized difference red edge (NDRE) data for three soybean lots with different irrigation methods (subsurface drainage, conventional, subsurface drip irrigation) using drone remote sensing. Combining NDVI (photosynthetically active biomass, PAB) and NDRE (chlorophyll) offered a comprehensive analysis of soybean growth, capturing both overall health and stress responses. Our analysis revealed distinct growth patterns for each lot. LotA(subsurface drainage) displayed early vigor and efficient resource utilization (peaking at NDVI 0.971 and NDRE 0.686), likely due to the drainage system. Lot B (conventional cultivation) showed slower growth and potential limitations (peaking at NDVI 0.963 and NDRE 0.681), suggesting resource constraints or stress. Lot C (subsurface drip irrigation) exhibited rapid initial growth but faced later resource limitations(peaking at NDVI 0.970 and NDRE 0.695). By monitoring NDVI and NDRE variations, farmers can gain valuable insights to optimize resource allocation (reducing costs and environmental impact), improve crop yield and quality (maximizing yield potential), and address rural challenges in South Korea. This study demonstrates the promise of drone-based VIs for revitalizing open-field agriculture, boosting farm income, and attracting young talent, ultimately contributing to a more sustainable and prosperous future for rural communities. Further research integrating additional data and investigating physiological mechanisms can lead to even more effective management strategies and a deeper understanding of VI variations for optimized crop performance.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.66-66
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• 2023

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.9-24
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• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.