• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.23-36
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• 2015

The temperature change patterns of climatic solar terms and their climatic fitness were analyzed. Harmonic analysis based on thirty-year(1981-2010) time-series data from sixty one weather stations across South Korea showed that the central peaks of the extreme heat had shifted toward start of autumn with increasing mean temperature. The overall climatic fitness of solar terms, such as major heat, frost descent, major snow, and major cold, was low, and it showed significant regional variations. The actual meteorological phenomenon representing each climatic solar term was observed much later than the day of the solar term at most weather stations. The number of observations, where an actual meteorological condition for each climatic solar term was recorded within ${\pm}1$ week from the day of that solar term, ranged only from 7.7% to 40.4% of the entire data. Study results also showed that the climatic fitness of major heat, frost descent, and major snow gradually changed in the east-west direction. Major cold, a solar term with higher climatic fitness, was influenced more strongly by latitude than longitude. Considering geographically uneven magnitude and trends in temperature changes, rearrangement and adjustment of time intervals between the solar terms may help us improve their applicability as realistic indicators of seasonal changes.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.3
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• pp.223-236
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• 2016

The objective of this study was to construct Italian ryegrass (IRG) dry matter yield (DMY) estimation models in South Korea based on climatic data by locations. Obviously, the climatic environment of Jeju Island has great differences with Korean Peninsula. Meanwhile, many data points were from Jeju Island in the prepared data set. Statistically significant differences in both DMY values and climatic variables were observed between south areas of Korean Peninsula and Jeju Island. Therefore, the estimation models were constructed separately for south areas of Korean Peninsula and Jeju Island separately. For south areas of Korean Peninsula, a data set with a sample size of 933 during 26 years was used. Four optimal climatic variables were selected through a stepwise approach of multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the selected four climatic variables and cultivated locations as dummy variables was constructed. The model could explain 37.7% of the variations in DMY of IRG in south areas of Korean Peninsula. For Jeju Island, a data set containing 130 data points during 17 years were used in the modeling construction via the stepwise approach of multiple regression analysis. The model constructed in this research could explain 51.0% of the variations in DMY of IRG. For the two models, homoscedasticity and the assumption that the mean of the residuals were equal to zero were satisfied. Meanwhile, the fitness of both models was good based on most scatters of predicted DMY values fell within the 95% confidence interval.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.65-81
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• 2019

The twenty-four Solar Terms are Chinese traditional astronomical divisions that describe seasonal cycles of the year. Based on the analyses of meteorological data during 1979~2018, study results showed that the temperatures of the Solar Terms had increased in general in the Korean Peninsula. In North Korea, temperature increases were observed on 21 Solar Terms, and their seasonal mean temperatures were increased by $0.87^{\circ}C$, $1.19^{\circ}C$, $1.45^{\circ}C$, and $0.64^{\circ}C$ on average in spring, summer, fall, and winter, respectively. The duration of summer has lengthened due to the temperature rise in fall, and the magnitude of temperature change was greater in summer compared to winter. As for South Korea, increases in temperature were observed on 18 Solar Terms, and the temperature changes were more pronounced in fall and winter than spring and summer. The Great Snow temperature decreased more than any other Solar Terms during the study period, and this temperature change was observed both in North and South Koreas. The Great Cold, which represents the coldest day of the year, showed a significant temperature increase of $3.08^{\circ}C$, while the Slight Heat had a marginal temperature increase of $0.29^{\circ}C$. The hottest day and the first day of frost tended to come later than the Great Heat and the Frost's Decent. By contrast, the coldest day tended to occur later than the Great Cold in the study area. On average over the entire study period, the climatic fitness of the Great Heat and the Frost's Decent was higher in North Korea, and that of the Great Cold was higher in South Korea, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.450-456
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• 2017

This study was conducted to develop estimated equation for mortality rates (volume of dead trees, %) on coniferous and broad-leaved forests, representative forest types of South Korea. There were 6 equation models applied for estimating mortality such as a exponential equation, a Hamilton equation and variables using were DBH, basal area, and site index. Raw data used for estimating mortality were $5^{th}$ and $6^{th}$ national forest inventory data, and mortality was calculated with the difference of stocks between lived trees and dead trees by each sample plots. The most applicable equation to describe mortality on coniferous forest and broad-leaved forest was indicated as $P=(1+e^{(a+b{\times}DBH+c{\times}BA+d{\times}no\_ha+e{\times}density)})^{-1}$ and their goodness of fit showed 34% and 51% respectively. Goodness of fit in both equations were not much high because there were various factors which affect the mortality such as topographic conditions, soil characteristic, climatic factors, site quality, and competition. Therefore, it is considered that explaining mortality in forest with only 2 or 3 variables like DBH, basal area used in this analysis could be very difficult facts. However, this study is certainly worth in that there is no useful information on mortality by each forest type throughout the country at the present, and we would make an effort to promote the fitness of estimated equation for mortality adding competition index, tree crown density etc.

• Korean Journal of Environmental Agriculture
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• v.13 no.3
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• pp.251-261
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• 1994

This study was conducted to get some basic information about rice plant development rate and heading ecology in various climatic conditions, growing nine varieties at three locations, Jinbu as the mountainous cool area, Suweon and Iri as the plain area for two years from 1987 to 1988. Average daily air temperature and day length from transplanting to heading date were analyzed in relation to the heading. Heading date and development rate of each variety were estimated by the Symplex method and the fitness of the model was evaluated. The results obtained as follows: Average daily air temperatures among varieties during the period from transplanting to heading ranged from 18 to $19^{\circ}C$ in Jinbu, from 22.5 to $23.5^{\circ}C$ in Suweon, and from 23.5 to $24.5^{\circ}C$ in Iri, the late-maturing varieties requiring the higher temperatures. The average heading days were about 20 days longer in Jinbu and $3{\sim}5$ days shorter in Iri than those in Suweon in all varieties. Little differences in accumulated temperature from transplanting to heading were observed in regions and years, and also among varieties. Developmental stages could be expressed as the accumulation of daily development rate and the predicted heading dates by the Symplex method were similar to the observed ones. The development rate of each variety varies with air temperatures. The early maturing Japonica types including the Unbong variety were fast in development rate at lower temperatures, but the late-maturing varieties of the Japonica type were late. A model to predict the heading dates of rice varieties by the Symplex method using air temperatures and day lengths was feasible.