• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.892-902
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• 2015

Agri-food ICT(Information and Communications Technologies) convergence has been raised as an important issue for agricultural industry competence. In this situation, this study is to enhance agricultural competitiveness and seek to development plan for agricultural corporation by diagnosing informatization level. For this purpose, this study conducted survey on informatization level of 3,019 agricultural corporations and calculated level score. And result is compared with SMEs(Small and Medium Enterprise) informatization survey, including manufacturing and service industries, conducted by Korea Technology & Information Promotion Agency for SMEs in recent agricultural corporations' growing with automation of agricultural production and improving service to customer satisfaction. Evaluation system is established to calculate informatization level score and AHP(Analytic Hierarchy Process) method was used by the experts to investigate weighting of assessment area, assessment indicators, assessment items. As a result, agricultural corporation informatization level score was 40.16 points which is lower than the benefitted organization of agri-food IT convergence modeling(43.44 points). By assessment area, the informatization level of promotional environment area was low and investment and training items were analyzed low especially so need to improve urgently. In the analysis result by organization type, agricultural company corporation's informatization level was higher than the agricultural association corporation and 'Processing and distribution' was higher than others by business type. Informatization level of agricultural corporation is 80 percent of 2013 SMEs' level(50.18 points) and 59.4 percent of a large corporation(67.64 points). In particular, big difference is occurred in investment feasibility analysis, informatization investment and education which will be need to improve.

• 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.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.187-206
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• 2020

Under the on-going evolution of the COVID-19 pandemic, estimating the economic impact of the pandemic is highly uncertain and challenging. This situation makes it difficult for policymakers, governors, and economic entities to formulate appropriate responses and decision makings. To provide useful information about the effect of the COVID-19 pandemic on the Korean economy, this study examined macroeconomic impact analysis stemming from the pandemic shocks with different scenarios for the Korean economy. Based on three scenarios using the growth rate of 2020 GDP and consumer expenditure patterns, the 2021 GDP by industry sector was forecast with two new approaches. First, the recovering process of the Korean economy from the shock was analyzed by applying a Flex-IO method. Second, a new forecasting approach combined with an IO coefficient matrix was applied to forecast the future GDP changes. The findings of this study are summarized as follows: First, the total GDP growth rate under the Pessimistic Scenario demonstrates less rebound from the shock than that of the Base Scenario. Second, agriculture, culture, and tourism-related sectors that are suffering from the severe losses of COVID-19 showed lower resilience than other different industries. Third, information and communications technology (ICT) industry maintains a stable growth trend and is expected to take the leading role for the Korean economy in the post-COVID-19 and the Industry 4.0 eras. The findings deliver that it needs to analyze how government expenditure responding the shock into the forecasting model, which can be more useful and reliable to simulate the resilience from the pandemic.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.395-404
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• 2019

This paper investigated the changes in Hanwoo breeding farms and herds according to their farm size and farm types based on traceability data in the Hanwoo industry. The major results are summarized as follows. First, the notion that small sized farms are breeding farms and middle or large sized farms are fattening farms is wrong. The results show that middle or large farms are not only fattening cattle but also breeding female cattle. Based on cattle data for over 6 months and under the criteria of a female cow ratio of 10 and 90% using the 2/4 quarter of 2018, the results show that the ratio of fattening only farms is 5.7%, that of breeding only farms is 59.0%, and that of fattening and breeding farms is 36.1%. The ratios of fattening, breeding, and both are 13.3, 13.5, and 73.2%, respectively, for a farm size with over 100 cattle. Second, this study found that the ratio of breeding farms over total farms has been increasing continuously over the last 5 years. This trend is apparent in the middle or large sized farms. However, the birth rate of cows is relatively lower in the middle and large sized farms than in the small sized farms. Hence, we can infer that the demand for a detection system for standing estrus in female cattle will increase. Additionally, the government should prepare relevant policies to stabilize the managerial conditions of middle or large sized farms.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.15-23
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• 2020

While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.137-152
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• 2023

Data is indispensable for digital transformation of agriculture with the development of innovative information and communication technology (ICT). In order to devise and prioritize strategies for enhancing data competitiveness in the agricultural sector, we employed an Analytic Hierarchy Process (AHP) analysis. Drawing from existing research on data competitiveness indicators, we developed a three-tier decision-making structure reflecting unique characteristics of the agricultural sector such as farmers'awareness of the data industry or awareness of agriculture among data workers. AHP survey was administered to experts from both agricultural and non-agricultural sectors with a high understanding of data. The overall composite importance, derived from the respondents, was rated in the following order: 'Employment Support', 'Data Standardization', 'R&D Support', 'Start-up Ecosystem Support', 'Relaxation of Regulations', 'Legislation', and 'Data Analytics and Utilization Technology'. In the case of experts in the agricultural sector, 'Employment Support' was ranked as the top priorities, and 'Legislation', 'Undergrad and Grad Education', and 'In-house Training' were also regarded as highly important. On the other hand, experts in the non-agricultural sector perceived 'Data Standardization' and 'Relaxation of Regulations' as the top two priorities, and 'Data Center' and 'Open Public Data' were also highly rated.

• Journal of Agricultural Extension & Community Development
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• v.15 no.2
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• pp.367-398
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• 2008

This study analyzed the disparity between the supply and demand of information demand and information provision generated among information providers(agricultural researchers) and information adopters(farmers), the two subjects of the local innovation diffusion process, with a focus on the contents and methods of sharing information and according to individual innovation diffusion pattern. In information provision, the characteristics of the contents of information in terms of their temporal necessity and effective period were more important than the field to which the contents of information belonged. In addition, the selection and strategic provision of an information provision method appropriate to each pattern according to the contents of information were proposed as a way of resolving farmers'information demand and strengthening their links to experiment stations. According to the analysis, information provision methods such as the limited use of some patterns in methods of providing documents, provision of production information using experiment field, and eco-friendly agricultural information to all types through regular study group sessions, search for plans for using ICT, and supplementary and interconnected composition of individual information provision methods were applicable in a complex manner according to the situation and management format, and the standard here was the contents of information.

• Journal of the Korean Institute of Rural Architecture
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• v.25 no.1
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• pp.17-24
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• 2023

There are various issues in rural areas. There are population decline, aging, and the absence of jobs and amenities. The government continues to expand various projects for rural areas. Recently, the government is promoting smart village projects in farming and fishing villages. The purpose of smart village is safety, convenience, smartization, and productivity improvement. The purpose of this study is to investigate the project and implementation process of smart villages, and domestic and foreign cases. And it classifies smart villages and suggests implementation strategies. The conclusion is as follows. ①The smart village business focuses on safety, living convenience, facility smartization, and agriculture and fisheries. ②In overseas cases, the smart village project focuses on improving the residential environment of farming and fishing villages in the EU, the UK, and Germany. Japan focuses on improving energy and agricultural and fisheries productivity. ③It is recommended that the smart village business be subdivided and promoted as much as possible. And the project enhances synergy in cooperation with other government ministries. ④Smart services increase credibility through FGI for public officials and residents. ⑤The project is carried out in consideration of agricultural products, tourism festivals, natural environment, history and tradition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3083-3098
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• 2023

As demands for efficient and echo-friendly production of marine products increase, smart aquaculture based on information and communication technology (ICT) has become a promising trend. The smart aquaculture is expected to control fundamental farm environment variables including water temperature and dissolved oxygen (DO) levels with less human intervention. A recirculating aquaculture system (RAS) is required for the smart aquaculture which utilizes a purification tank to reuse water drained from the water tank while blocking the external environment. Elaborate water treatment should be considered to properly operate RAS. However, analyzing the water treatment performance is a challenging issue because fish farm circumstance continuously changes and recursively affects water fluidity. To handle this issue, we introduce computational fluid dynamics (CFD) aided water treatment analysis including water fluidity and the solid particles removal efficiency. We adopt RAS parameters widely used in the real aquaculture field to better reflect the real situation. The simulation results provide several indicators for users to check performance metrics when planning to select appropriate RAS without actually using it which costs a lot to operate.