• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.185-199
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• 2019

Korea's facility horticulture has developed remarkably in a short period of time. However, in order to secure international competitiveness in response to unfavorable surrounding conditions such as high operating costs and market opening, it is necessary to diagnose the problems of facility horticulture and prepare countermeasures through analysis. The purpose of this study was to analyze the case of leading farmers by introducing information and communication technology (ICT) in hydroponic cultivation agriculture and horticulture, and to examine how agricultural technology utilizing smart farm and big data of facility horticulture contribute to farm productivity. Crop growth information gathering and analysis solutions were developed to analyze the productivity change factors calculated from hydroponics tomato farms and strawberry farms. The results of this study are as follows. The application range of the leaf temperature was verified to be variously utilized such as house ventilation in the facility, opening and closing of the insulation curtain, and determination of the initial watering point and the ending time point. Second, it is necessary to utilize water content information of crop growth. It was confirmed that the crop growth rate information can confirm whether the present state of crops is nutrition or reproduction, and can control the water content artificially according to photosynthesis ability. Third, utilize EC and pH information of crops. Depending on the crop, EC values should be different according to climatic conditions. It was confirmed that the current state of the crops can be confirmed by comparing EC and pH, which are measured from the supplied EC, pH and draining. Based on the results of this study, it can be confirmed that the productivity of smart farm can be affected by how to use the information of measurement growth.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.505-514
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• 2019

Our country is making efforts to manage water resources efficiently. In the future, It is necessary to develop a plan after subdividing the basin considering regional problems and water use, topographical and climatic characteristics. This study constructed water supply and demand system based on the standard watershed unit for water shortage evaluation considering spatial resolution. In addition, water shortage were calculated and compared using the MODSIM model in the Han-river basin. As a result, the average water shortage occurring during the 49 years (1967-2015) was 129.98 million $m^3$ for the middle watershed unit and 222.24 million $m^3$ for the standard watershed unit, resulting in a difference of about 2.1 billion m3. However, the trends and distribution of water shortage occurrence were very similar. The reason for this is that, in the case of the Middle watershed unit analysis, water shortages are calculated for the demand for living, industrial, and agricultural water for the representative natural flow value, assuming that all the water can be used in basin. The standard basin unit analysis showed that the difference between the fractionated supply and demand resulted in a large water shortage due to the relatively small amount of available water, and that the main stream did not show water shortage due to the ripple effect of the return flow. If the actual water use system is considered in the model as well as the subdivision of the spatial unit, it will be possible to evaluate the water supply and demand reflecting the regional characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.456-463
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• 2019

Micro climatic conditions within the livestock facility are affected by various factors such as ventilation, cooling, heating, insulation and latent and sensible heat generation from animals. In this study, numerical BES method was used to simulate energy flow inside the poultry house. Based on the BES method and THI concept, degree of thermal stress of poultry was evaluated according to the locations in South Korea. Comparison of THI values within the poultry house was also carried out according to the stocking densities to reflect recent animal-welfare issue. Significant decrease in thermal stress of poultry was observed when the stocking density of $30kg/m^2$ was applied in the change of the seasons(p<0.05) however, there was no statistically significant difference in summer season(p>0.05). It meant that installation of proper cooling system is urgently needed. For Iksan city of Jeollabuk-do province, total 252 hours of profit for thermal stress was found according to decrease in the stocking density.

• Journal of the Korean Society of Earth Science Education
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• v.12 no.1
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• pp.27-39
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• 2019

The purpose of this study is to develop a STEAM program for teaching climate change through CLAMP (Climate-Leaf Analysis Multivariate Program) paleoclimate inquiry in connection with high school 'Integrated Science' subject. In order to do so, we analyzed the 2015 revised national curriculum and science textbook in terms of the PDIE instructional design model, and developed the teaching-learning materials for 10 class hours through expert panel discussion and pilot test. According to the STEAM class procedure, in the situation presentation stage, the fossil leaves were collected from the dicotyledon plants near school, and the LMA (Leaf Margin Analysis) climate inquiry activity. was presented as the learning goal. During the creative design stage, students were taught about geology and leaf fossils in the study region, and CLAMP input data (31 characteristics of morphotype and leaf architectural of fossil leaves) were given. In the emotional experience and new challenge stage, we collected leaf fossils for outdoor learning, explored paleoclimate with CLAMP method, and promoted climatic literacy in the process of discussing tendencies and causes of Cenozoic's climate change. The validity of the development program was assessed (CVI .84) as being suitable for development purpose in all items through the process of establishing reliability among expert panel. In order to apply the program to the high school, a pilot test was conducted to supplement the discrepancies and to review the suitability. The satisfaction rate of the participants was 4.48, and the program was complemented with their opinions. This study will enable high school students to have practical knowledge and reacting volition for climate change, and contribute to fostering students' climate literacy.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.33-42
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• 2011

It was analyzed climatic data in Gimje, Buan, Iksan and Jeonju in Jeonbuk Province between 1930s and 1990s. The data source of Gimje and Iksan in 1930s were Namseon Agricultural Experimental Station. Those in 1990s was Honam Agricultural Research Institute, Rural Development Administration. The data source of Jeonju of 1930s and 1990s was Jeonju Weather Station, Korea Meteorological Administration. Weather Station of Gimje and Buan were located at the agricultural area in rural paddy field. That of Iksan was located at the agricultural area in suburban paddy field. That of Jeonju was located at the downtown area. As compared to mean air temperature between 1930s and 1990s, it was increased by $0.2^{\circ}C$ in agricultural area, $0.6^{\circ}C$ in Iksan city and $1.4^{\circ}C$ in Jeonju city. On the while, increased temperature was the higher in winter than other seasons. Annual precipitation was increased by 128.1 mm in agricultural area and 169.3 mm in Jeonju city. And it was remarkable in summer season.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.957-972
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• 2018

Tunnels constructed in cold regions can cause serious defects such as cracks and leaks due to external temperature changes in the portals and vents. In order to prevent the freezing damage of the tunnel, appropriate measures should be applied to the section where the freeze damage is concerned. However, the specific criteria and contents for judging whether or not the anti-freeze measures are applied are not presented. In this study, the laboratory freezing tests on the temperature changes of the concrete specimens under freezing conditions were carried out. And the freeze-thaw repetition cycle (F), which can judge the possibility of freezing damage, were presented based on the heat transfer quantity (W) by experimental results of case studies. Also, we propose a classification of cold regions considering the climatic characteristics of Korea for using it to efficient design and maintenance.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.91-107
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• 2018

It is required to monitor and assess the desertification in Tunisia, where the Sahara Desert, which is located in the southern part of Tunisia, is recently expanding northward. In this study, by using remote sensed data, land cover changes were examined, and the Normalized Difference Vegetation Index (NDVI), Topsoil Grain Size Index (TGSI) and Albedo are used to monitor and assess desertification in Tunisia. Decision Tree was constructed, and the frequencies and trends of each assessment indicator, desertification degree and land cover were identified. In addition, we analyzed the correlation between assessment indicators and precipitation. As a result, desertification is generally intensifying northward, especially in areas with high levels of desertification. Also, bivariate correlation analysis showed that Albedo, NDVI and TGSI were all highly correlated with precipitation. It indicates that changes in precipitation have also been shown to affect Tunisian desertification. In conclusion, this study has improved the usability of various methodologies considering the assessment indicators based on satellite imagery, Decision Tree, which is a method of evaluating them complexly, and trends of land cover change.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.672-679
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• 2018

This study was conducted to predict the potential distribution and risk of invasive alien plant, Amaranthus patulus, in an agricultural area of South Korea. We collected 254 presence localities of A. patulus using field survey and literature search and stimulated the potential distribution area of A. patulus using maximum entropy modeling (MaxEnt) with six climatic variables. Two different kinds of agricultural risk index, raster risk index and regional risk index, were estimated. The 'raster risk index' was calculated by multiplying the potential distribution by the field area in $1{\times}1km$ and 'regional risk index' was calculated by multiplying the potential distribution by field area proportion in the total field of South Korea. The predicted potential distribution of A. patulus was almost matched with actual presence data. The annual mean temperature had the highest contribution for distribution modeling of A. patulus. Area under curve (AUC) value of the model was 0.711. The highest regions were Gwangju for potential distribution, Jeju for 'raster risk index' and Gyeongbuk for 'regional risk index'. This different ranks among the index showed the importance about the development of various risk index for evaluating invasive plant risk.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.75-84
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• 2019

In this study, the random forest approach was used to predict the national mean rice yield of South Korea by using mean climatic factors at a national scale. A random forest model that used monthly climate variable and year as an important predictor in predicting crop yield. Annual yield change would be affected by technical improvement for crop management as well as climate. Year as prediction factor represent technical improvement. Thus, it is likely that the variables of importance identified for the random forest model could result in a large error in prediction of rice yield in practice. It was also found that elimination of the trend of yield data resulted in reasonable accuracy in prediction of yield using the random forest model. For example, yield prediction using the training set (data obtained from 1991 to 2005) had a relatively high degree of agreement statistics. Although the degree of agreement statistics for yield prediction for the test set (2006-2015) was not as good as those for the training set, the value of relative root mean square error (RRMSE) was less than 5%. In the variable importance plot, significant difference was noted in the importance of climate factors between the training and test sets. This difference could be attributed to the shifting of the transplanting date, which might have affected the growing season. This suggested that acceptable yield prediction could be achieved using random forest, when the data set included consistent planting or transplanting dates in the predicted area.