• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.151-171
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• 2023

This study analyzed farmer's responses to the pilot project in advance of the nationwide expansion of the farm-customized early warning service for weather risk management by conducting a survey among all farmers who received text messages of this service. We analyzed not only the satisfaction of farmers with the early warning service, but also the effectiveness of the service in preventing agrometeorological disasters through cross-tabulation analysis of survey results. More than 330 farmers participated in the survey, and more than 60% of the respondents said that they had prevented or mitigated crop disasters by using the early warning service. The cross-tabulation analysis showed that farmers who perceived the field-specific weather information of the early warning service to be more accurate than the weather forecast were statistically significantly more likely to prevent crop disasters than those who did not. According to our case study, farmers who grew open field fruit crops were particularly sensitive to weather information and confirmed that early warning services, along with disaster prevention facilities, were effective in preparing for freezing and frost injury that had been occurring frequently under the influence of climate change. This study is significant in that it is the first to systematically analyze the effectiveness of the farm-customized early warning service for weather risk management based on extensive surveys. It is expected to contribute to exploring ways to develop the service ahead of the nationwide expansion of the early warning service in the near future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.290-305
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• 2015

To improve the practicality of 'Early warning service about agrometeorological weather hazards' and operation efficiency to deliver site-specific about a lot of land unit possibility of weather hazard occurrence with the suitable counterplan to farmer, site-specific early warning service system that was built at the National Academy of Agricultural Science in Korea passed some of the error supplementation and service's stabilization stage during operation period for trial services from October 2014 to March 2015. Field service system covered about 470 volunteered farmer and 950 lots in Seomjin river downstream areas (part of Gwangyang-si, Hadong-gun, Gurye-gun). This system (Two track system) consists of early warning system (a lot of land unit) to inform farmer by individual text message and dispersal prior alert system that can see the jurisdiction's situation of local government. Individual text message about Seomjin river downstream that is our first study area was launched since $2^{nd}$ March 2015, and online site (http://www.agmet.kr) started business since April 2015. Service offers currently information of farm weather, farm weather hazard, nationwide weather risk and special weather alert, also our system will consistently expand the service target area and contents and improve the service quality until 2017 when our study finished. To prevent crops damage that was caused by crisis situation like farm weather and weather damage offer prior alert about agrometeorological weather harzard to volunteered farmer, thereby our study expects to help the reduction of farm's damage caused by weather derivatives.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.214-215
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• 2014

Recently, Russia decided to export an annual 7.5 million tons of natural gas to Korea over 30 years from 2015, as also deal with China, planed to build a pipeline connecting Siberia to Shandong Peninsula about 4000km. Risk management is required depending on the project in extreme cold weather, because it is concerned about the behavior of the seasonal changes in soil temperature and the strain of pipe according to the long-distance pipeline construction. The plan of data management shall be prepared in parallel for a sophisticated risk management, because a data is massive scale and it is generated/accumulated in real time. Therefore, this research is aimed to classify a data items in engineering stage of pipeline by previous studies for managing a generated data depending on the detail works in extreme cold weather. We expect to be provided the foundation of an efficient classification system of a generated data from the pipeline project life cycle.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.133-144
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• 2017

Recently, weather information is getting closer to our real life, and it is a very important factor especially in the transportation field. Although the damage caused by the abnormal climate changes around the world has been gradually increased and the correlation between the road risk and the possibility of traffic accidents is very high, the domestic research has been performed at the level of basic research. The Purpose of this study is to develop a risk map for the road hazard forecasting service of weather situation by linking real - time weather information and traffic information based on accident analysis data by weather factors. So, we have developed a collection and analysis about related data, processing, applying prediction models in various weather conditions and a method to provide the road hazard map for national highways and provincial roads on a web map. As a result, the road hazard map proposed in this study can be expected to be useful for road managers and users through online and mobile services in the future. In addition, information that can support safe autonomous driving by continuously archiving and providing a risk map database so as to anticipate and preemptively prepare for the risk due to meteorological factors in the autonomous driving vehicle, which is a key factor of the 4th Industrial Revolution, and this map can be expected to be fully utilized.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.257-264
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• 1991

Korea has accomplished the afforestation of its forest land in the early 1980's. To meet the increasing demand for forest products and forest recreation, a development of scientific forest management system is needed as a whole. For this purpose the development of efficient forestfire management system is essential. In this context, the purpose of this study is to develop a theoretical foundation of forestfire danger rating system. In this study, it is hypothesized that the degree of forestfire risk is affected by Weather Factor and Man-Caused Risk Factor. (1) To accommodate the Weather Factor, a statistical model was estimated in which weather variables such as humidity, temperature, precipitation, wind velocity, duration of sunshine were included as independent variables and the probability of forestfire occurrence as dependent variable. (2) To account man-caused risk, historical data of forestfire occurrence was investigated. The contribution of man's activities make to risk was evaluated from three inputs. The first, potential risk class is a semipermanent number which ranks the man-caused fire potential of the individual protection unit relative to that of the other protection units. The second, the risk sources ratio, is that portion of the potential man-caused fire problem which can be charged to a specific cause. The third, daily activity level is that the fire control officer's estimate of how active each of these sources is, For each risk sources, evaluate its daily activity level ; the resulting number is the partial risk factor. Sum up the partial risk factors, one for each source, to get the unnormalized Man-Caused Risk. To make up the Man-Caused Risk, the partial risk factor and the unit's potential risk class were considered together. (3) At last, Fire occurrence index was formed fire danger rating estimation by the Weather Factors and the Man-Caused Risk Index were integrated to form the final Fire Occurrence Index.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.

• Korean Journal of Veterinary Service
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• v.32 no.3
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• pp.287-292
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• 2009

This study was conducted to analyse risk factors which can influence on blood splash in slaughtered cattle in D slaughterhouse located in Gyeonggi province in 2008. A total of 13,056 cattle were studied by several risk factors such as species, gender, body weight, meat grade, weather (temperature), transport distance, lairaging time, moving time, mixing cattle from different sources. As the result of analysis, the total mean of blood splash was 0.70% and the rate was highest (0.94%) in castrated Hanwoo. The heavier body weight, the higher blood splash rate. The farms which have had more than one experience of blood splash tend to have high grade in meat quality. As a weather factor, the rate in summer season was lower than in winter season. It increased as transport distance getting longer and decreased when the lairaging time was 2~5 hours. We could know many risk factors strongly related with the occurrence of blood splash from this study.

• The Plant Pathology Journal
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• v.28 no.2
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• pp.172-184
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• 2012

An infection risk model for Phytophthora blight on chili pepper was developed to estimate the first date of disease occurrence in the field. The model consisted of three parts including estimation of zoosporangium formation, soil water content, and amount of active inoculum in soil. Daily weather data on air temperature, relative humidity and rainfall, and the soil texture data of local areas were used to estimate infection risk level that was quantified as the accumulated amount of active inoculum during the prior three days. Based on the analysis on 190 sets of weather and disease data, it was found that the threshold infection risk of 224 could be an appropriate criterion for determining the primary infection date. The 95% confidence interval for the difference between the estimated date of primary infection and the observed date of first disease occurrence was $8{\pm}3$ days. In the model validation tests, the observed dates of first disease occurrence were within the 95% confidence intervals of the estimated dates in the five out of six cases. The sensitivity analyses suggested that the model was more responsive to temperature and soil texture than relative humidity, rainfall, and transplanting date. The infection risk model could be implemented in practice to control Phytophthora blight in chili pepper fields.

• The Plant Pathology Journal
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• v.39 no.5
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• pp.504-512
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• 2023

After transitioning from periodic to model-based control policy for fire blight blossom infection, it is crucial to provide the timing of field application with easy and accurate information. To assess the risk of blossom infection, Maryblyt was employed in 31 sites across apple-producing regions nationwide, including areas prone to fire blight outbreaks, from 2021 to 2023. In 2021 and 2023, two and seven sites experienced Blossom Infection Risk-Infection warning occurrences among 31 sites, respectively. However, in 2022, most of the sites observed Blossom Infection Risk-Infection from April 25 to 28, highlighting the need for blossom infection control. For the comparison between the two model-based control approaches, we established treatment 1, which involved control measures according to the Blossom Infection Risk-Infection warning and treatment 2, aimed at maintaining the Epiphytic Infection Potential below 100. The analysis of control values between these treatments revealed that treatment 2 was more effective in reducing Blossom Infection Risk-Infection and the number of days with Epiphytic Infection Potential above 100, with respective averages of 95.6% and 93.0% over the three years. Since 2022, the implementation of the K-Maryblyt system and the deployment of Automated Weather Stations capable of measuring orchard weather conditions, with an average of 10 stations per major apple fire blight county nationwide, have taken place. These advancements will enable the provision of more accurate and timely information for farmers based on fire blight models in the future.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.213-217
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• 2009

Weather factors affect cost increases and progress management under construction. Because progress schedule is delayed by weather factors, the construction costs are increased. It is an essential element to control the progress schedule applying weather factors to the progress management. This study applies monthly working-day percentages which is estimated by databases of past weather information to RTPM system. Through do progress management in construction projects exactly, will try to minimize risk of process control that do that is to weather factors. Also, will compare calamity in safety supervision side that do that is to weather factors beforehand. Based on the factors and the expected impact of factors together with the weather data during the last 50 years in Seoul region gathered from Korea. Through it, calculated number of month working day of RCA's structural steel work. Studied way that apply to RTPM system.