• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.627-646
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• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Korean Journal of Environment and Ecology
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• v.35 no.6
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• pp.594-600
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• 2021

The purpose of this study is to observe the period of mating calls of cicadas in South Korea to identify the emergence period and geographic distribution for each cicada species. The study sites were 19 protection areas nationwide. The mating calls of cicadas were collected over the 12 months of 2019. A bioacoustics measuring device was installed to record the mating calls of cicadas in WAV, 44,100Hz format for 1 minute every hour. The temperature was recorded once or twice every hour using a micro-meteorological measuring device. Nine species of Korean cicadinae were studied. The start and end periods of mating calls were recorded for each cicada species for the subsequent analysis. The analysis results showed that nine cicada species appeared in the 19 protection areas. The chronological order of mating call periods for each species was as follows: Cryptotympana atrata (7/12 - 9/30), Meimuna opalifera (7/27 - 10/20), Hyalessa fuscata (7/25 - 10/9), Graptopsaltria nigrofuscata (7/28 - 9/5), Platypleura kaempferi (7/3 - 9/29), Suisha coreana (9/14 - 10/30), Leptosemia takanonis (6/26 - 8/2), Auritibicen intermedius (7/27 - 9/28), and Meimuna mongolica (8/8 - 9/11). The mating call period was between 35 (Meimuna mongolica) and 89 (Platypleura kaempferi) days, with the average being 62 days. The elevation above sea level for the habitats of each species was as follows: 5 - 386 m for Cryptotympana atrata, 7 - 759 m for Meimuna opalifera, 7 - 967 m for Hyalessa fuscata, 42 - 700m for Graptopsaltria nigrofuscata, 7 - 700 m for Platypleura kaempferi, 5 - 759 m for Suisha coreana, 7 - 759 m for Leptosemia takanonis, 397 - 967 m for Auritibicen intermedius, and 7 - 42 m for Meimuna mongolica. The average temperature of the habitats of each species was as follows: 23.9℃ for Cryptotympana atrata, 21.8℃ for Meimuna opalifera, 22℃ for Hyalessa fuscata, 23℃ for Graptopsaltria nigrofuscata, 22.9℃ for Platypleura kaempferi, 14.6℃ for Suisha coreana, 20.6℃ for Leptosemia takanonis, 19.3℃ for Auritibicen intermedius, and 24.4℃ for Meimuna mongolica. In terms of the habitat distribution of species, Meimuna opalifera, Hyalessa fuscata, and Platypleura kaempferi were distributed in more than 15 protection sites. Cryptotympana atrata was distributed in the lowlands in the southwest. Graptopsaltria nigrofuscata was distributed in the western area of the Korean Peninsula. Suisha coreana was distributed in areas excluding high mountain areas and parts of the southeast area. Leptosemia takanonis was distributed in areas near the mountains. Auritibicen intermedius was distributed locally in the high mountain areas. Meimuna mongolica was distributed locally in flat wetlands.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.246-254
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• 2022

Domestic facility agriculture grows rapidly, such as modernization and large-scale. And the production scale increases significantly compared to the area, accounting for about 60% of the total agricultural production. Greenhouses require energy input to create an appropriate environment for stable mass production throughout the year, but the energy load per unit area is large because of low insulation properties. Through the rooftop greenhouse, one of the types of urban agriculture, energy that is not discarded or utilized in the building can be used in the rooftop greenhouse. And the cooling and heating load of the building can be reduced through optimal greenhouse operation. Dynamic energy analysis for various environmental conditions should be preceded for efficient operation of rooftop greenhouses, and about 40% of the solar energy introduced in the greenhouse is energy exchange for crops, so it should be considered essential. A major analysis is needed for each sensible heat and latent heat load by leaf surface temperature and evapotranspiration, dominant in energy flow. Therefore, an experiment was conducted in a rooftop greenhouse located at the Korea Institute of Machinery and Materials to analyze the energy exchange according to the growth stage of crops. A micro-meteorological and nutrient solution environment and growth survey were conducted around the crops. Finally, a regression model of leaf temperature and evapotranspiration according to the growth stage of leafy vegetables was developed, and using this, the dynamic energy model of the rooftop greenhouse considering heat transfer between crops and the surrounding air can be analyzed.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.1-22
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• 2022

The modification effects of street trees on outdoor thermal comfort in summertime according to tree planting types and road direction were analyzed using a computer simulation program, ENVI-met. With trees, the air temperature and wind speed decreased, and the relative humidity increased. In the case of mean radiant temperature (T_mrt) and human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI), there was a decrease during the daytime. The greatest change among the meteorological factors by trees happened in Tmrt, and PET and UTCI showed similar patterns with T_mrt·The most effective tree planting type on thermal comfort modification was low tree height, wide tree crown, high leaf area index, and narrow planting interval (LWDN). T_mrt, PET and UTCI showed a large difference depending on shadow patterns of buildings and trees according to solar altitude and azimuth angles, and building locations. When the building shade areas increased, the thermal modification effect by trees decreased. In particular, results on the east and west sidewalks showed a large deviation over time. When applying the LWDN, the northwest, west and southwest sidewalks showed a significant reduction of 8.6-12.3℃ PET and 4.2-4.5℃ UTCI at 10:00, and the northeast, east and southeast sidewalks showed 8.1-11.8℃ PET and 4.4-5.0℃ UTCI at 16:00. On the other hand, when the least effective type (high tree height, narrow tree crown, low leaf area index, and wide planting interval) was applied, the maximum reduction was up to 1.8℃ PET and 0.9℃ UTCI on the eastern sidewalks, and up to 3.0℃ PET and 0.9℃ UTCI on the western ones. In addition, the difference in modification effects on T_mrt, PET and UTCI between the tree planting types was not significant when the tree effects were reduced by the effects of buildings. These results can be used as basic data to make the most appropriate street tree planting model for thermal comfort improvement in urban areas in summer.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.485-496
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• 2022

Modern agriculture is being transformed into smart agriculture to maximize production efficiency along with changes in the 4th industrial revolution. However, rural areas in Korea are facing challenges of aging, low fertility, and population outflow, making it difficult to transition to smart agriculture. Among ICT technologies, simulation allows users to observe or experience the results of their choices through imitation or reproduction of reality. The combination of the three-dimension (3D) model and the greenhouse simulator enable a 3D experience by virtual greenhouse for fruits and vegetable cultivation. At the same time, it is possible to visualize the greenhouse under various cultivation or climate conditions. The objective of this study is to apply the greenhouse climate management model for simulation development that can visually see the state of the greenhouse environment under various micrometeorological properties. The numerical solution with the mathematical model provided a dynamic change in the greenhouse environment for a particular greenhouse design. Light intensity, crop transpiration, heating load, ventilation rate, the optimal amount of CO₂ enrichment, and daily light integral were calculated with the simulation. The results of this study are being built so that users can be linked through a web page, and software will be designed to reflect the characteristics of cladding materials and greenhouses, cultivation types, and the condition of environmental control facilities for customized environmental control. In addition, environmental information obtained from external meteorological data, as well as recommended standards and set points for each growth stage based on experiments and research, will be provided as optimal environmental factors. This simulation can help growers, students, and researchers to understand the ICT technologies and the changes in the greenhouse microclimate according to the growing conditions.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.36-58
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• 2022

In this study, the weather conditions corresponding to the increase in the environmental concentration of fine dust (PM₁₀) and ultrafine dust (PM_2.5) from 2001 to 2019 in Jeju and Seogwipo cities were analyzed. The increase in the levels of PM₁₀ and PM_2.5 was observed in the order: spring > winter > autumn > summer. In both cities, PM₁₀ and PM_2.5 levels increased more frequently during the day in spring and summer and at night in autumn and winter, with PM_2.5 showing a greater increase in concentration than PM₁₀. The air temperature and wind speed corresponding with increased levels of PM₁₀ were higher than their respective seasonal averages in spring and winter, but lower in summer and autumn. Relative humidity was lower than the seasonal average during all seasons. The air temperature variation corresponding with increased levels of PM_2.5 showed the same seasonal trend as that observed for PM₁₀. The relative humidity was higher than the respective seasonal averages in spring and summer, and lower in winter. The wind speed was lower than the seasonal average in both the cities. When the PM₁₀ and PM_2.5 levels increased, the wind direction was from the north and the west during the day and varied according to the season at night. The rate of the increase in the PM₁₀ concentration was the highest in both cities at the wind speed of 1.6 - 3.4 ms^-1 during the day and night except during night in the summer. The highest concentration of PM_2.5 was observed with the wind speed range of 1.6 - 3.4 ms^-1 in Jeju, and 0.3 - 1.6 ms^-1 in Seogwipo. The results of this study applied to urban and landscape planning will aid in the formulation of strategies to reduce the adverse effects of fine particular matter.

• Atmosphere
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• v.33 no.2
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• pp.223-246
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• 2023

This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Korean journal of applied entomology
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• v.24 no.3 s.64
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• pp.123-127
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• 1985

Incidence of the Fusarium wilt caused by F. oxysporum f. sp. vasinfectum of sesame (var. Kwangsan) was remarkably influenced by seeding date and mean air temperature in the field of two or three year's continuous cropping with sesame in 1983 and 1985. Sesame were seeded on six different dates from April 20 to July 5. Air temperature was checked daily at the meteorological station near the experimental field. Low($16{\sim}20^{\circ}C$) and high temperature($20{\sim}25^{\circ}C$) periods were provisionally devided, based on every ten-day mean daily temperature during field experiment for last ten years, which corresponded to before and after June 15 in Jinju, Gyeong-nam. Infection rates were 83.7%, 68.2% and 59.4% in the plants grown for 55 days (seeding date: April 20), 40 days(May 5) and 25 days(May 20) under low temperature. On the other hand, infection rates were below 3% in those plots seeded during high temperature period. The longer the growth period exposed to low temperature, the higher was infection rates. It is interesting to note that 40 days old seedling or older are prone to severe infection compared to the younger ones, in higher temperature of $20{\sim}25^{\circ}C$. Therefore, seedlings in vegetative growth stage are less prone to infection than these in reproductive growth stage. The result showed that air temperature during sesame growth was one of the most important factor affecting the incidence of Fusarium wilt. This suggested that sesame crop, which is of tropical origin, has been predisposed to Fusarium wilt, when the plants were exposed to low temperature of $16{\sim}20^{\circ}C$.