• Journal of the Korean Wood Science and Technology
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• 제45권2호
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• pp.202-212
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• 2017

This study was to establish the interrelation between chemical compositions and near infrared (NIR) spectra for the classification on distinguishability of domestic gymnosperms. Traditional wet chemistry methods and infrared spectral analyses were performed. In chemical compositions of five softwood species including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cypress (Chamaecyparis obtusa), and cedar (Cryptomeria japonica), their extractives and lignin contents provided the major information for distinction between the wood species. However, depending on the production region and purchasing time of woods, chemical compositions were different even though in same species. Especially, red pine harvested from Naju showed the highest extractive content about 16.3%, whereas that from Donghae showed about 5.0%. These results were expected due to different environmental conditions such as sunshine amount, nutrients and moisture contents, and these phenomena were also observed in other species. As a result of the principal component analysis (PCA) using NIR between five species (total 19 samples), the samples were divided into three groups in the score plot based on principal component (PC) 1 and principal component (PC) 2; group 1) red pine and Korean pine, group 2) larch, and group 3) cypress and cedar. Based on the chemical composition results, it was concluded that extractive content was highly relevant to wood classification by NIR analysis.

• 대한교통학회지
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• 제19권6호
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• pp.65-73
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• 2001

교통량이 시간의 흐름과 관련이 있는 시계열 데이터라는 개념을 기초로 교통량 패턴을 시계열 분석을 사용하여 분해해 보고자 하였다. 교통량 패턴은 추세치(T)와 계절변동(S), 주기변동(C), 그리고 불규칙변동(I)으로 구분할 수 있었는데 본 연구에서는 불규칙변동을 기상요인을 통해 설명하려는 시도를 하였다. 왜냐하면 교통의 주체인 사람들 행태의 특성상 기상의 변화와 관련이 깊다고 판단을 내렸기 때문이었다. 기상요인으로는 일우량, 일조량, 풍속, 주야율 강설량, 기온 등 여러 가지가 있지만 교통량의 변화와 가장 관련이 깊다고 여겨지는 일우량과 최저기온을 이용하였다. 일단 시계열 성분을 분해하고 나면 이를 이용하여 AADT를 추정하게 되는데, 추정의 결과를 비교하기 위해 AADT 추정방법을 두 가지로 구분하였다. 즉, 기상요인을 사용했을 경우와 그렇지 않을 경우로 나누어 결과를 살펴보았다. 추정 결과를 비교하는 척도로는 RMSE와 U-test를 사용하였다. 결과를 보면 불규칙변동요인을 그대로 사용했을 때보다, 기상요인을 결합한 불규칙변동요인을 사용했을 때 더 추정력이 좋았다. 이것은 각 조사지점의 RMSE와 U-test값을 구한 후 그 지점의 AADT로 나누어 준 결과를 보고 알 수 있었다. 이 연구를 통해 우리는 불규칙변동요인 이용방법의 중요성에 대해 한번 더 생각해 보게 된다. 즉 그것을 설명하는 방법에 의해 기존보다 더 나은 모형을 얻을 수도 있다는 결론에 이르게 된다는 것이다.

• 농업생명과학연구
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• 제45권4호
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• pp.29-35
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• 2011

본 연구에서는 2005년부터 2009년까지 전라남도 지역의 기상변화와 산불특성과의 관련성을 파악하기 위해 기상요소와 산불 발생자료 (시간, 원인)를 분석한 결과, 최고온도 상승과 상대습도 감소로 인해 산불발생의 위험성이 높은 기후조건이 형성되었으며, 산불은 최고기온 $10{\sim}20^{\circ}C$에서, 상대습도 40~60% 에서, 평균풍속 2 m/s이하에서 주로 발생하였다. 이러한 기상조건은 강우 후에 2~3일이면 산불발생 위험이 높은 기상조건이 형성되었다.

• 화훼연구
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• 제19권1호
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• pp.37-41
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• 2011

본 실험은 여름철에 비해 상대적으로 광도가 감소되는 시기인 8월 이후부터 익년 3월까지 차광처리가 팔레놉시스의 잎과 뿌리의 생육 그리고 화경의 발생에 미치는 영향에 대하여 조사하였다. 차광처리는 자연광의 50%, 60%, 70%, 80%, 그리고 90% 수준이었다. 야간 $CO_2$의 흡수량과 증산량, 엽내 탄수화물함량, 생체중과 건물중 모두 50%와 60% 차광에서 높았으며 70%수준 이상에서는 차광이 증가할수록 감소하였다. 화경의 길이, 개체당 화경수와 소화수는 50%와 60% 차광에서 다른 처리보다 높았으며 개화소요일수도 짧았다. 특히, 90%수준에서는 화경의 발생이 현저하게 억제될 뿐만 아니라 실험기간 동안 개화는 이루어지지 않았다.

• 한국농공학회논문집
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• 제61권6호
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

• 한국토양비료학회지
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• 제21권1호
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• pp.11-14
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• 1988

옥수수 군락상(群落上)에서 측정(測定)한 순복사량(純輻射量)과 일사량(日射量), 온도(氣溫)의 관측치(觀測値)를 이용(利用)하여 일사량(日射量)과 순복사량(純輻射量)의 관계식을 구하고 복사수지식(輻射收支式)의 각항(各項)에 관(關)한 경험식(經驗式)을 이용(利用)하여 주간순복사량(晝間純輻射量)으르 추정(推定)하는 모델을 제안(題案)하였으며 결과(結果)를 요약(要約)하면 다음과 같다. 1. 일사량(日射量)과 주간순복사량(晝間純輻射量)의 관계식(關係式)은 $R_n(+)=0.6659$ $R_s$로 일사량(日射量)과 주간복사량(晝間純輻射量)의 비율(比率)이 66%이상(以上)이었다. 2. 일조율(日照率)이 35%이상(以上)인 흐린날의 일사량(日射量)과 주간순복사량(晝間純輻射量)의 관계식(關係式)은 $R_n(+)=0.7295{\cdot}R_s$로 흐린날에 옥수수 군락(群落)의 일사량(日射量)에 대(對)한 주간순복사량비율(晝間純輻射量比率)이 약간 큰 경향(傾向)이었다. 3. 복사수지식(輻射收支式)을 이용(利用)하여 일사량(日射量)과 기온(氣溫)으로 주간순복사량(晝間純輻射量)의 추정식(推定式) {$(0.9R_s-(352-227{\times}10^{-10}{\times}Ta^4) (1.11R_s/R_{so}-0.05)$}을 얻었다.

• 수산경영론집
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• 제52권2호
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• pp.55-67
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• 2021

Global warming affects critical natural resources, one of which is the oceans that occupy 70% of the total cover of the earth. In other words, ocean warming is a subset of global warming which needs to be addressed urgently. Purple laver (pyropia spp.) is one of the most vulnerable items to climate change although it is a major export product of Korean fisheries. The purpose of this study is to analyze the causality of how climate change caused by global warming affects the increase or decrease of PLP (purple laver production). The target area for analysis was set to Maro-hae between Jindo-gun and Haenam-gun. We selected marine environmental factors and meteorologic factors that could affect PLP as variables, as well as co-integration tests to determine long-term balance, and the Granger causticity tests. As a result, PLP and marine environmental factors WT (water temperature), pH, and DO confirmed that long-term equilibrium relationships were established, respectively. However, there is only causality with WT and it is confirmed that there is only a correlation between pH and DO (dissolved oxygen). There was no long-term equilibrium relationship between PLP and HDD (heating degree days) and there is a causal effect that HDD affects PLP; however, it was less clear than that of WT. The relationship between PLP and RF (rainfall), WS (wind speed), SS (percentage of sunshine), and FF (farm facilities) was all balanced in the long term, and causality exists. Based on the results of the analysis, policy proposals were made.

• 한국기후변화학회지
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• 제6권4호
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• pp.277-281
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• 2015

A Chinese cabbage is one of important vegetables which accounts for more than 60 percent of leaf vegetable. However, cultivation area and yield of Chinese cabbage are steadily decreasing recently. Because meteorological changes destabilize the balance of Chinese cabbage, we need to study on meteorological factors affecting estimation of Chinese cabbage yield. So we conducted a panel analysis using mean temperature, maximum temperature, minimum temperature, precipitation and sunshine's duration from August to November for estimation of Chinese cabbage yield. As the results, we found that if the mean temperature of September increase by $1^{\circ}C$ the amount of production of Chinese cabbage per unit area was increased by 348.6 kg/10a. We also found that the mean temperature of October increased by 174.8 kg/10a, that of November 148 kg/10a, the difference between the maxium temperature and the minimum temperature of October equals 443.3 kg/10a. However, we found that the difference between the maximum temperature and the minimum temperature of November decreased 274.1 kg/10a.

• 한국환경과학회지
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• 제28권8호
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

• Journal of Animal Science and Technology
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• 제63권1호
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• pp.77-90
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• 2021

This study aimed to assess the impact of abnormal climate events on the production of Italian ryegrass (IRG), such as autumn low-temperature, severe winter cold and spring droughts in the central inland, southern inland and southern coastal regions. Seasonal climatic variables, including temperature, precipitation, wind speed, relative humidity, and sunshine duration, were used to set the abnormal climate events using principal component analysis, and the abnormal climate events were distinguished from normal using Euclidean-distance cluster analysis. Furthermore, to estimate the impact caused by abnormal climate events, the dry matter yield (DMY) of IRG between abnormal and normal climate events was compared using a t-test with 5% significance level. As a result, the impact to the DMY of IRG by abnormal climate events in the central inland of Korea was significantly large in order of severe winter cold, spring drought, and autumn low-temperature. In the southern inland regions, severe winter cold was also the most serious abnormal event. These results indicate that the severe cold is critical to IRG in inland regions. Meanwhile, in the southern coastal regions, where severe cold weather is rare, the spring drought was the most serious abnormal climate event. In particular, since 2005, the frequency of spring droughts has tended to increase. In consideration of the trend and frequency of spring drought events, it is likely that drought becomes a NEW NORMAL during spring in Korea. This study was carried out to assess the impact of seasonal abnormal climate events on the DMY of IRG, and it can be helpful to make a guideline for its vulnerability.