• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.29-37
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• 2012

An experiment for an optimized automatic greenhouse environment in a flower farming greenhouse by building a ubiquitous sensor network with various sensors was conducted and the results were evaluated. And various culturing environmental information and data in the greenhouse were collected and analyzed. Then, the greenhouse was designed to maintain the best culturing environment on the basis of existing recommended optimized figures. By measuring the growth of the crops in the greenhouse, A system which controls facilities in the greenhouse to maintain the best culturing environment in accordance with change in the environment was analyzed.Computer simulation result proced that we discovered that controlling the facilities and the artificial light source increased production, enhanced quality, reduced labor and heating cost immensely. The experiment has proved that the u-flower farming system can maximize the income of farm families by sending warning messages to users of this system when weather suddenly changes so that users may cope with such changes and maintain the best culturing environment.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.603-611
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• 2020

Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.901-912
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• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.899-907
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• 2022

According to the Unmanned aircraft system Traffic Management (UTM), drones are permitted to fly up to 150m above ground, which is located in the atmospheric boundary layer where there is considerable wind fluctuation due to turbulence. Although it is difficult to predict when turbulence will occur drone aviation safety could be enhanced by having a better understanding of the characteristics of vertical profile of wind in the flight area. We used wind lidar (WIndMast 350M) to observe vertical profiles of wind at the test site for aviation meteorological observation equipment located near Incheon International Airport in July and September, 2022. In this study, we utilized the observed wind profile data to propose a technique for obtaining information that could help improve the drone aviation safety. The Fourier transform analysis is used to evaluate the temporal characteristics of the horizontal wind speed at various vertical levels up to 350m. We also examined the relative contribution of the variance of wind having scales of less than an hour, a crucial scale for drone flight, to the variance of wind having all scales at each vertical altitude for days with and without precipitation.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.40-53
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• 2021

Research vessels(R/Vs) used for ocean research move to the planned research area and perform ocean observations suitable for the research purpose. The five research vessels of the Korea Institute of Ocean Science & Technology(KIOST) are equipped with global positioning system(GPS), water depth, weather, sea surface layer temperature and salinity measurement equipment that can be observed at all times during cruise. An information platform is required to systematically manage and utilize the data produced through such continuous observation equipment. Therefore, the data flow was defined through a series of business analysis ranging from the research vessel operation plan to observation during the operation of the research vessel, data collection, data processing, data storage, display and service. After creating a functional design for each stage of the business process, KIOST Underway Meteorological & Oceanographic Information System(KUMOS), a Web-Geographic information system (Web-GIS) based information platform, was built. Since the data produced during the cruise of the R/Vs have characteristics of temporal and spatial variability, a quality management system was developed that considered these variabilities. For the systematic management and service of data, the KUMOS integrated Database(DB) was established, and functions such as R/V tracking, data display, search and provision were implemented. The dataset provided by KUMOS consists of cruise report, raw data, Quality Control(QC) flagged data, filtered data, cruise track line data, and data report for each cruise of the R/V. The business processing procedure and system of KUMOS for each function developed through this study are expected to serve as a benchmark for domestic ocean-related institutions and universities that have research vessels capable of continuous observations during cruise.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.132-140
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• 2005

This study was conducted to develop regional site index equations for main tree species in Gangwon, Gyunggi-Chungcheong, Gyungsang, and Jeolla area of Korea, using environmental and soil factors obtained from a digital forest site map. Using the large data set obtained from the digital forest map, a total of 28 environmental and soil factors were regressed on site index by tree species for developing the best site index equations for each of the regions. The selected main tree species were Larix 1eptolepis, Pinus koraiensis, Pinus densiflora, Pinus thunbergii, and Quercus acutissima. Finally, four to five environmental and soil factors by species were chosen as independent variables in defining the best regional site index equations with the highest coefficients of determination $(R^2)$. For those site index equations, three evaluation statistics such as mean difference, standard deviation of difference and standard error of difference were applied to the data sets independently collected from fields within the region. According to the evaluation statistics, it was found that the regional site index equations by species developed in this study conformed well to the independent data set, having relatively low bias and variation. It was concluded that the regional site index equations by species had sufficient capability for the estimation of site productivity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.11-21
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• 2014

The purpose of this study was to furnish basic information for forest community ecology and to accumulate vegetational datum related to hierarchy of forest community for the efficient management of forest vegetation in Mt. Mani. Samples were collected and analyzed by 32 releves from August to October in 2010 using phytosociological analysis methodology of Z-M school and importance value analysis. The results were summarized that the forest vegetation was classified into 5 units in total. Importance value at vegetation unit 1 indicated Pinus densiflora 54.31 (18.10%), Quercus mongolica 39.21 (13.07%), Carpinus coreana 37.29 (12.43%), at vegetation unit 2 Quercus mongolica 89.43 (22.23%), Rhododendron mucronulatum 57.75 (14.43%), Carpinus coreana 47.19(11.80%), at vegetation unit 3 Styrax japonica 53.97 (13.50%), Acer mono 33.60 (8.40%), Carpinus coreana 26.48 (6.62%), Quercus serrata 22.51 (5.64%), at vegetation unit 4 Carpinus coreana 47.70 (11.92%), Quercus acutissima 38.40 (9.60%) and at vegetation unit 5 Evodia daniellii 80.59 (20.14%), Robinia pseudoacacia 35.00 (8.74%), Pueraria thunbergiana 28.63 (7.15%), Quercus dentata 28.20 (7.05%) in the order, respectively.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.297-307
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• 2011

This study investigates relation of food safety incidents with climate. Therefore food safety incidents and climate data during 1999 to 2009 have been analyzed. In situ observations of monthly mean temperature, maximum temperature, minimum temperature, precipitation, and relative humidity in 60 observation stations of Korean Meteorological Administration (KMA) have been used in this study. Food safety incidents data have been constructed by searching media reports following Park's method (2009) during the same period. According to the Park's method, 729 events were collected. To analyze its relations, food safety incidents data have been classified into chemical, biological, and physical hazards. Pearson product-moment correlation coefficients have been applied to analyze the relations. The correlation of food safety incidents has negative one with precipitation (-0.48), and positive one with minimum temperature(0.45). Precipitation has been correlated with biological and physical hazards more than chemical hazard. Temperatures (mean temperature, maximum temperature, and minimum temperature) have been correlated closely with chemical hazard than others. Food safety incidents data has been interblended with human behavior factor through decision-making processes in food manufacturing, processing, and consumption phases of "farm-totable" food processing. Act in the preventing damage will be obvious if the hazard were apparent. Therefore abnormal condition could be more dangerous than that of apparent extreme events because apparent events or extreme events become one of alarm over hazards. Therefore, human behavior should be considered as one of the important factors for analysis of food safety incidents. The result of this study can be used as a better case study for food safety researches related to climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.1-30
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• 2024

The international community adopts the SSP (Shared Socioeconomic Pathways) scenario as a new greenhouse gas emission pathway. As part of efforts to reflect these international trends and support for climate change adaptation measure in the agricultural sector, the National Institute of Agricultural Sciences (NAS) produced high-resolution (1 km) climate change scenarios for the Korean Peninsula based on SSP scenarios, certified as a "National Climate Change Standard Scenario" in 2022. This paper introduces SSP climate change scenario of the NAS and shows the results of the climate change projections. In order to produce future climate change scenarios, global climate data produced from 18 GCM models participating in CMIP6 were collected for the past (1985-2014) and future (2015-2100) periods, and were statistically downscaled for the Korean Peninsula using the digital climate maps with 1km resolution and the SQM method. In the end of the 21^st century (2071-2100), the average annual maximum/minimum temperature of the Korean Peninsula is projected to increase by 2.6~6.1℃/2.5~6.3℃ and annual precipitation by 21.5~38.7% depending on scenarios. The increases in temperature and precipitation under the low-carbon scenario were smaller than those under high-carbon scenario. It is projected that the average wind speed and solar radiation over the analysis region will not change significantly in the end of the 21st century compared to the present. This data is expected to contribute to understanding future uncertainties due to climate change and contributing to rational decision-making for climate change adaptation.