• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Journal of Biosystems Engineering
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• v.33 no.2
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• pp.106-114
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• 2008

This study was performed to analyze the distribution of air current speed, $CO_2$ concentration, and photosynthetic photon flux (PPF) in a closed transplants production system (CTPS) for producing quality transplants. And the effect of PPF on the growth of potato (Solanum tuberosum L. cv. Dejima) plug seedlings was analyzed. Uniformity of the air current speed in CTPS was improved by installing perforated floors in duct for air circulating and by adjusting of air flow rate of the fan connected to air conditioning unit used in this study, Measured $CO_2$ concentrations were measured $409{\pm}13$, $950{\pm}25$, and $1,550{\pm}35\;{\mu}mol{\cdot}mol^{-1}$ for setting values of 400, 950, and $1,550\;{\mu}mol{\cdot}mol^{-1}$, respectively. Uniformity of PPF by adding each one the single fluorescent lamp of 20 W at both ends of the single fluorescent lamps of 40 W was highly improved. While the average PPF measured under the twin fluorescent lamps of 55 W installed at regular intervals of 10 cm was decreased by increasing the vertical distance from the lighting sources, the ratio of average PPF measured at both ends to PPF measured in the center was 74-79%. Five levels ($100{\pm}9$, $150{\pm}14$, $200{\pm}17$, $250{\pm}24$ and $300{\pm}31{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$) of PPF were provided to investigate the effect of PPF on plant height, fresh weight and dry weight of potato plug seedlings produced in CTPS. Plant height was decreased by increasing PPF. Maximum fresh weight and dry weight were shown under PPF of $250{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$. Thus PPF of $250\;{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ was enough to produce quality potato transplants under air temperature, photoperiod, and relative humidity of $20^{\circ}C$, 16/8 h, and 70%, respectively. It was concluded that quality indices such as plant height, fresh weight and dry weight could be improved by illuminating of adequate PPF from artificial lighting sources.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.2
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• pp.142-149
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• 1995

This study was conducted to investigate the relationships between yearly variation of climatic components and yearly variations of productivity in monoculture cotton. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components from the four varieties(Kinggus, Yongdang local. 113-4, 380) were collected from 1978 to 1992 in Mokpo area. The meteorological data gathered at the Mokpo Weather Station for the same period were used to find out the relationships between climatic components and productivity. Yearly variation of the amount of precipitation and number of stormy days in July are large with coefficients of the variations(C.V)84.89 and 97.05%, respectively, while yearly variation, of the average temperature, maximum temperature, minimum temperature from May to Sep. are relatively small. Seed cotton yield before frost in Sep. and Oct. very greatly with C.V. of 68.77, 78.52%, respectively. Number of boll bearing branches and lint percentage show more or less small in C.V. with 11.77 and 19.13%, respectively and flowering date and boll opening date show still less variation. Correlation coefficients between precipitation in May and number of boll bearing branches, duration of sunshine in July and number of bolls per plant, maximum temperature in July and total seed cotton before the frost in Sep., Oct., and Nov. evaporation in Aug. are positively sig-nificant at the 1% level. There are highly significantly positive correlated relationships among yield(total seed cotton) and yield components. Total seed cotton yield(Y) can be predicted by multiple regression equation with independent variables of climatic factors in July such as monthly averages of average temperature($X_1$), maximum temperature($X_2$) and minimum temperature($X_3$), monthly amount of precipitation ($X_4$), evaporation($X_5$), monthly average of relative humidity($X_6$), monthly hours with sunshine($X_7$) and number of rainy days($X_8$). The equation is estimatedas Y =-1080.8515 + 144.7133$X_1$+15.8722$X_2$ + 164.9367$X_3$ + 0.0802$X_4$ + 0.5932$X_5$ + 11.3373$X_6$ + 3.4683$X_7$- 9.0846$X_8$. Also, total seed cotton yield(Y) can be predicted by the same method with climatic components in Aug., Y =2835.2497 + 57.9134$X_1$ - 46.9055$X_2$ - 41.5886X$_3$ + 1.2559$X_5$ - 21.9687$X_6$ - 3.3763$X_7$- 4.1080$X_8$- 17.5586$X_9$. And the error between observed and theoretical yield were less with approached linear regression.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.105-113
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• 2001

This study was conducted to reveal the effects of local climatic conditions on the vegetative growth in a mature stand of Korean white pine based on climatic estimates. For this, the annual increments of stand variables such as DBH, height, basal area and volume were measured and estimated for seven years from 1974 to 1980. The local climatic conditions in the study site were also estimated by both a topoclimatological method and a spatial statistical technique. The local climatic conditions were then correlated with and regressed on the growth factors to reveal the relationships between the climatic estimates and the growth. It is found that relatively high temperatures had positive effects on the diameter growth. The yearly diameter growth increased when each of mean, maximum, and minimum temperature during the growing season was high. Height growth showed positively significant correlation with three climatic variables. The most important variable influencing height growth was the average of maximum temperature for 10 months from January to October. It means that the higher the average of maximum temperature for 10 months from January to October is, the more height growth of Korean white pine increases. Other climatic variables related to height growth were average of minimum temperature for 3 months in the early growing season and mean relative humidity for the growing season. Six climatic variables related to temperature had effects on basal area increment and all of them were positively correlated with basal area increment. Especially, temperatures from January to March were important factors affecting the basal area increment. In volume increment, high correlation was also recognized with most of temperature variables. This tendency was the same as the results in diameter and hight increments. This means that the volume growth increases when temperatures during the growing season are relatively high.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• Journal of Korean Society of Forest Science
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• v.84 no.3
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• pp.277-285
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• 1995

This study was conducted to understand the relationship between climatic factors and matsutake(Tricholoma matsutake) mushroom production. Data on local annual matsutake production collected from 29 locations from 1984 to 1993 were analyzed for stepwise and multiple regression with local climatic data, such as monthly maximum, minimum, and average air temperature, soil temperature, relative humidity, amount of rainfall, and number of rainy days. Correlation between monthly climatic factors and annual matsutake production was calculated in each location(Case 1), each year(Case 2), and each month(Case 3). In Case 1, number of rainy days and minimum temperature in Sep. showed positive correlation with matsutake production. In Case 2, maximum, minimum, and average temperature in June showed negative correlation with matsutake production. In Case 3, amount of precipitation in Sep. and Oct. number of rainy days in Sep., and minimum temperature in Sep. and Oct. showed positive correlation with matsutake production. In conclusion, amount of rainfall and number of rainy days in Sep. were the most important climatic factors and correlated positively with matsutake production. Below average air temperature in June was also beneficial for matsutake production.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.1
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• pp.89-96
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• 2014

We aimed to evaluate the effects of climatic elements on potato yield and create a model with climatic elements for estimating the potato yield, using the results of the regional adjustment tests of potato. We used 86 data of the yield data of a potato variety, Sumi, from 17 regions over 11 years. According to the results, the climatic elements showed significant level of correlation coefficient with marketable yield appeared to be almost every climatic elements except wind velocity, which was daily average air temperature (Tave), daily minimum air temperature (Tmin), daily maximum air temperature(Tmax), daily range of air temperature (Tm-m), precipitation (Prec.), relative humidity (R.H.), sunshine hours (S.H.) and days of rain over 0.1 mm (D.R.) depending on the periods of days after planting or before harvest. The correlations between these climatic elements and marketable yield of potato were stepwised using SAS, statistical program, and we selected a model to predict the yield of marketable potato, which was $y=7.820{\times}Tmax_-1-6.315{\times}Prec_-4+128.214{\times}DR_-8+91.762{\times}DR_-3+643.965$. The correlation coefficient between the yield derived from the model and the real yield of marketable yield was 0.588 (DF 85).

• Journal of Energy Engineering
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• v.25 no.3
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• pp.66-72
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• 2016

In this study, a sulfonated poly(arylene ether ketone) block copolymer was prepared from hydrophilic oligomer and hydrophobic oligomer. The structure of the prepared membrane was characterized by $^1H$-NMR, FT-IR and GPC. The $M_w$(weight-average molecular weights) of the polymer was $209,700g\;mol^{-1}$ and the molecular weight distribution($M_w/M_n$) of 1.25 was obtained. The prepared membrane showed excellent thermal stability with gradual weight loss up to $200^{\circ}C$. The proton conductivity of SPAEK block copolymer reached the maximum of $9.0mS\;cm^{-1}$ at $90^{\circ}C$ under 100% relative humidity (RH). From the observed results, it is necessary to do more aggressive attempt to study the possibility of application as an ion-conductive composite electrolyte.

• Water for future
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• v.28 no.6
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• pp.147-158
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• 1995

The purpose of this study is to establish a method of estimating the daily urban water demand using statistical model. This method will be used for the development of the efficient management and operation of the water supply facilities. The data used were the daily urban water use, the population, the year lapse and the weather conditions such as temperature, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. The raw data used in this study were rearranged either by month or by season for the purpose of analysis, and the statistical analysis was applied to the data to obtain the regression model. As a result, the multiple linear regression model was developed to estimate the daily urban water use based on the seather condition. The regression constant and the model coefficients were determined for each month of a year. The accuracy of the model was within 3% of average error and within 10% of maximum error. The developed model was found to be useful to the practical operation and management of the water supply facilities.

• Current Research on Agriculture and Life Sciences
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• v.3
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• pp.28-35
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• 1985

This work Was carried out to obtain the most suitable crop coefficient for the paddy rice growing in Taegu area. The result was due to the comparative measurements of evapotranspiration formula in terms of Blaney & Criddle and eight other formulas with those produced by experiment particularly in this area. The crop coefficient, evapotranspiration and transpiration ratio produced by this research are hopefully expected to be of service in the future calculation of evapotranspiration without repeating experiment respectively, whenever the water requirement of paddy rice is planned in Taegu and its vicinity. The accomplished results could be summarized as follows : The maximum amount of evapotranspiration was recorded in the early and middle parts of August. The average reading of evapotranspiration was 6.33mm/day throughout the growth. The evapotranspiration had a highly significant correlation with pan evaporation, solar radiation, sunshine hours and relative humidity of meteorological elements. K and Kc by the use of Blaney & Criddle formula calculated at 0.76 to 1.45 and 0.82 to 1.27, respectively. Its peak value appeared commonly in early August. The ratio of transpiration was 269.03.