• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.104-112
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• 2023

Agriculture plays an industrial and economic role, as well as an environmental and ecological conservation role, group harmony and the inheritance of traditional culture. However, no matter how advanced the industry is, the basic food necessary for human life can only be produced through the photosynthesis of plants with natural resources such as the sun, water, and air. The Food and Agriculture Organization of the United Nations (FAO) predicts that the world's population will increase by another 2 billion people by 2050, and it faces a myriad of complex and diverse factors to consider, including climate change, food security concerns, and global ecosystems and political factors. In particular, in order to solve problems such as increasing productivity and production of agricultural products, improving quality, and saving energy, it is difficult to solve them with traditional farming methods. Recently, with the wind of the 4th industrial revolution, ICT convergence technology and artificial intelligence have been rapidly developing in many fields, but it is also true that the application of new technologies is somewhat delayed due to the unique characteristics of agriculture. However, in recent years, as ICT and artificial intelligence utilization technologies have been developed and applied by many researchers, a revolution is also taking place in agriculture. This paper summarizes the current state of research so far in four categories of agriculture, namely crop cultivation environment management, soil management, pest management, and irrigation management, and smart farm research data that has recently been actively developed around the world.

• Journal of Agricultural Extension & Community Development
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• v.13 no.1
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• pp.49-67
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• 2006

The purpose of this study was to suggest development strategies of a village of Hwaseong-si where several programs using it's traditional items have been operated since 2003 according to the policy of Rural Traditional Thema Village Development implemented by Rural Development Administration(RDA). The village is located in Yodang-ri, Yanggam-myun, hwaseong-si in Gyounggi province. The village is called as 'Eunheng Namu Maeul' which means 'ginkgo tree village' since the tree is almost 350 years old and beautifully huge. Including this big tree there are much more traditional items such as organic dairy farming, hand-made cheese, legends and traditional plays. Using this items and government subsidies, the village has managed various tour programs and other income increasing projects. This study analyzed the strengths, weaknesses, opportunities and threats of the current situation of the village with the related materials and data to find out development strategies for the village-based programs and projects. This study recommended the followings as a major result of this study. The huge ginkgo tree at the village could be a better traditional attractive item when paths and wood of ginkgo trees will be built up especially utilizing the original huge one around the village. Like this, the item of hand made cheese could be a much more valuable traditional item when there will be an advanced facility for the people's working together. The social actives of the village have been weakened because of few young dwellers living there, therefore there needs a special subsidizing project for the village to hire a young manager having some social skills and knowledges. The situation being urbanized in front of the village needs precisely checking and implementing the Hwaseong-si's urbanization policy so that the urbanization could be harmonized with the maintenance and development of the traditional items of the village.

• Journal of Internet of Things and Convergence
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• v.3 no.1
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• pp.13-19
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• 2017

In this paper, we designed and implemented Thing Connected-Green, a self-installing agricultural automation system capable of remote monitoring and control based on Low Power Wide Area communication technology (LPWA). Farming requires water, sunlight, soil, fertilizer, temperature control, etc., and these elements can be remotely monitored and controlled using an automated system. Using this system, it is possible to construct an agricultural automation system which can be optimized according to the kind of plant and cultivation environment from vinyl house to flower garden. The information gathered from the sensor is stored in the server through the gateway, and the optimal cultivation environment can be set and operated using the smart phone based on the big data.

• Journal of Korean Society of Rural Planning
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• v.12 no.1 s.30
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• pp.23-35
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• 2006

The purpose of this study were to identify the different farming styles of red pepper growers, to describe their characteristics and to get some implications far planning the agricultural development strategy in the area. The researcher surveyed quantitative and qualitative data through interview with researcher developed questionnaires from selected 99 farmers in Eumsung county, Chungbuk province, Korea. The researcher found the low types of red pepper farming: 'red-pepper-centric middle farmers', 'diversified larger farmers', 'red-pepper-dependant small farmers', and 'small farmers for own use'. Based on the above findings, the researcher could derive some implications as follows. Firstly, the difference of market strategy and marketing efforts among the four farming styles should be regarded as important considerations when planning the agricultural development strategy in Emsung county. Secondly, the cooperatives' red pepper marketing strategies in Eumsung county were focused on the processed red pepper products sold at middle or low priced by big retailers in urban areas. Therefore, the cooperatives should change their view point of quality, if they want to initiate the planning process of 'the production and marketing high quality red pepper'. Thirdly, the major efforts of Eumsung county Agricultural Technology Center (ATC) made efforts on increasing the productivity of red pepper farming, however, the technologies recommended by the ATC for farmers required more cost and labour especially for 'red-pepper-dependant small farmers' and 'diversified large farmers'. The ATC should make efforts to find new technologies for helping 'red-pepper-dependant small farmers' to reduce the use of pesticides and 'diversified large farmers' to use the regional images effectively for marketing their hish quality red peppers.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.80-89
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• 2019

The purpose of this study is to analyze the relationship between SPI (Standardized Precipitation Index) meteorological drought and RDI (Reservoir Drought Index) agricultural drought for Geum river basin. Drought Indices was calculated by collecting data of precipitation and agricultural reservoir water storage rate from 2014 to 2016. To evaluated the correlation between meteorological and agricultural drought, the Pearson correlation and the Receiver Operation Characteristic (ROC) analysis were conducted to evaluate the correlation between meteorological and agricultural droughts. The SPI-6 and RDI showed the highest relationship with Pearson coefficient 0.606 and ROC hit rates 0.722 respectively, and the spatial occurrence patterns of drought using overlapped SPI-6 and RDI, the big differences between the 2 indices were occurred in the upstream areas of Miho stream and Nonsan stream from August to October 2015. The analysis using reservoirs specifications for areas where reservoir droughts occurred was conducted, and the areas showing severe drought of RDI were the reservoir areas having relatively small value of basin magnifying power (BMP). This means that a reservoir has the reaction capability for agricultural drought mainly depending on the reservoir BMP.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.507-519
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• 2013

This study is to evaluate agricultural water supply capacity in Geum river basin (9,865 $km^2$), one of the 5 big river basin of South Korea using MODSIM-DSS (MODified SIMyld-Decision Support System) model. The model is a generalized river basin decision support system and network flow model developed at Colorado State University designed specifically to meet the growing demands and pressures on river basin management. The model was established by dividing the basin into 14 subbasins and the irrigation facilities viz. agricultural reservoirs, pumping stations, diversions, culverts and groundwater wells were grouped and networked within each subbasin and networked between subbasins including municipal and industrial water supplies. To prepare the inflows to agricultural reservoirs and multipurpose dams, the Soil and Water Assessment Tool (SWAT) was calibrated using 6 years (2005-2010) observed dam inflow and storage data. By MODSIM run for 8 years from 2004 to 2011, the agricultural water shortage had occurred during the drought years of 2006, 2008, and 2009. The agricultural water shortage could be calculated as 282 $10^6m^3$, 286 $10^6m^3$, and 329 $10^6m^3$ respectively.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.939-949
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• 2020

Currently, the demand for farmland is steadily decreasing due to changes in the agricultural environment and dietary life. In line with this, the government adopted an integrated water management with the enactment of the Framework Act on Water Management on June 2019. Therefore, it is required to take a closer look at agricultural water demand that accounts for 61% of water use for efficient water resources management. In this study, the overal process was evaluated for estimating agricultural water demand. More specifically, agricultural water demand for paddy field, which comprises 67% to 87% of agricultural water demand, was reviewed in detail. The biggest issue in estimating the paddy field water demand is the selection of the method for potential evapotranspiration. FAO recommends Penman-Monteith, but, currently, our criteria suggest a modified Penman equation that shows over estimation. Also, the crop coefficient, which is the main factor in evaluating evapotranspiration, has an issue that does not consider the current climate and crop varieties because it was developed 23 years ago. Comparing the Modified Penman and Penman-Monteith equations using the data from Jeonju National Weather Service, the modified Penman equation showed a big difference compared to the Penman-Monteith equation. When the crop coefficient was applied, the difference between late May and late August increased, where the amount of evapotranspiration was high. The estimation process was applied to four study reservoirs in Gimje. Comparing the estimated water demand with the supplied water record from reservoirs, the results showed that the estimation accuracy depends on not just the potential evapotranspiration, but also the standard water storing level in paddy fields.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.2
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• pp.145-153
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• 2017

This study was aimed to find yield prediction model of Italian ryegrass using climate big data and geographic information. After that, mapping the predicted yield results using Geographic Information System (GIS) as follows; First, forage data were collected; second, the climate information, which was matched with forage data according to year and location, was gathered from the Korean Metrology Administration (KMA) as big data; third, the climate layers used for GIS were constructed; fourth, the yield prediction equation was estimated for the climate layers. Finally, the prediction model was evaluated in aspect of fitness and accuracy. As a result, the fitness of the model ($R^2$) was between 27% to 95% in relation to cultivated locations. In Suwon (n=321), the model was; DMY = 158.63AGD -8.82AAT +169.09SGD - 8.03SAT +184.59SRD -13,352.24 (DMY: Dry Matter Yield, AGD: Autumnal Growing Days, SGD: Spring Growing Days, SAT: Spring Accumulated Temperature, SRD: Spring Rainfall Days). Furthermore, DMY was predicted as $9,790{\pm}120$ (kg/ha) for the mean DMY(9,790 kg/ha). During mapping, the yield of inland areas were relatively greater than that of coastal areas except of Jeju Island, furthermore, northeastern areas, which was mountainous, had lain no cultivations due to weak cold tolerance. In this study, even though the yield prediction modeling and mapping were only performed in several particular locations limited to the data situation as a startup research in the Republic of Korea.