• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.76-84
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• 2013

An adequate downscaling of the official forecasts of Korea Meteorological Administration (KMA) is a prerequisite to improving the value and utility of agrometeorological information in rural areas, where complex terrain and small farms constitute major features of the landscape. In this study, we suggest a simple correction scheme for scaling down the KMA temperature forecasts from mesoscale (5 km by 5 km) to the local scale (30 m by 30 m) across a rural catchment, especially under temperature inversion conditions. The study area is a rural catchment of $50km^2$ area with complex terrain and located on a southern slope of Mountain Jiri National Park. Temperature forecasts for 0600 LST on 62 days with temperature inversion were selected from the fall 2011-spring 2012 KMA data archive. A geospatial correction scheme which can simulate both cold air drainage and the so-called 'thermal belt' was used to derive the site-specific temperature deviation across the study area at a 30 m by 30 m resolution from the original 5 km by 5 km forecast grids. The observed temperature data at 12 validation sites within the study area showed a substantial reduction in forecast error: from ${\pm}2^{\circ}C$ to ${\pm}1^{\circ}C$ in the mean error range and from $1.9^{\circ}C$ to $1.6^{\circ}C$ in the root mean square error. Improvement was most remarkable at low lying locations showing frequent cold pooling events. Temperature prediction error was less than $2^{\circ}C$ for more than 80% of the observed inversion cases and less than $1^{\circ}C$ for half of the cases. Temperature forecasts corrected by this scheme may accelerate implementation of the freeze and frost early warning service for major fruits growing regions in Korea.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.1
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• pp.207-244
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• 2015

Aviation safety is the stage in which the risk of harm to persons or of property damage is reduced to, and maintained at or below, an acceptable level through a continuing process of hazard identification and risk management. Many accidents and incidents have been taking place since 2014, while there had been relatively safer skies before 2014. International civil aviation community has been exerting great efforts to deal with these emerging issues, thus enhancing and ensuring safety throughout the world over the years. The Preamble of the Chicago Convention emphasizes safety and order of international air transport, and so many Articles in the Convention are related to the safety. Furthermore, most of the Annexes to the Convention are International Standards and Recommended Practices pertaining to the safety. In particular, Annex 19, which was promulgated in Nov. 2013, dealing with safety management system. ICAO, as law-making body, has Air Navigation Commission, Council, Assembly to deliberate and make decisions regarding safety issues. It is also implementing USOAP and USAP to supervise safety functions of member States. After MH 370 disappeared in 2014, ICAO is developing Global Tracking System whereby there should be no loophole in tracking the location of aircraft anywhere in world with the information provided by many stakeholders concerned. MH 17 accident drove ICAO to install web-based repository where information relating to the operation in conflict zones is provided and shared. In addition, ICAO has been initiating various solutions to emerging issues such as ebola outbreak and operation under extreme meteorological conditions. Considering the necessity of protection and sharing of safety data and information to enhance safety level, ICAO is now suggesting enhanced provisions to do so, and getting feedback from member States. It has been observed that ICAO has been approaching issues towards problem-solving from four different dimensions. First regarding time, it analyses past experiences and best practices, and make solutions in short, mid and long terms. Second, from space perspective, ICAO covers States, region and the world as a whole. Third, regarding stakeholders it consults with and hear from as many entities as it could, including airlines, airports, community, consumers, manufacturers, air traffic control centers, air navigation service providers, industry and insurers. Last not but least, in terms of regulatory changes, it identifies best practices, guidance materials and provisions which could become standards and recommended practices.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.266-271
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• 2012

This study was carried out to evaluate the land suitability for southern-type garlic cultivation associated with both temperature and soil constraints. The suitability analysis was conducted with hourly temperature data from 2001 to 2010 at all fifty seven meteorological stations and the soil-based suitability map of garlic provided by Rural Development Administration. Firstly the temperature data were processed by the growth stages (germinating, bulbing, and winter vegetation season), and then were adopted to limit the irrelevant lands. Next, as a result of overlaying each soil and temperature suitability map, the total 274,339 ha of area was mapped as highly suitable or suitable for southern-type garlic cultivation and the top four of the largest classified si-guns were identified as Naju, Jeongeup, Gochang, and Jinju. On the other hand, the statistical records of KOSIS (KOrea Statistical Information Service) showed lower amount of cultivation area than the analyzed results in the major production sites, Goheung, Sinan, Haenam, and Muan. However, it should not be regarded as exceptional because farmer's preference might not correspond to potential land usability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.116-126
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• 2013

Weather factor to affect driver's driving environment are due to changes in weather conditions is caused rainfall, snowfall, fog etc and the reducing of road capacity and because deteriorating weather could be affect the headway and vehicle speed and the decrease in lane caused by an accident occurs that was analyzed that bad weather occur congestion greater than on the clear day. Bad weather to reduce of the driver's visibility was analysed the sensitive to changes in travel speed and traffic accident to appears high characteristics according to weather conditions on the expressway(higher speed) than general road. As a result, visibility have been determined to be important factor in changes of the highway traffic flow characteristics. Therefore, in this study, we selected traffic volume and travle speed that have a major impact on high-speed expressway basic segments as importance effect factor and we selected to subject of analysis among the Metropolitan Expressway that it could be obtained certain level of traffic volume data and we studied the changing of expressway traffic flow due to change visibility after the collecting of meteorological and traffic data. In order to perform this study, data collection and analysis methods were established through the existing literature and we had selected level of visibility of the expressway and we had performed the statistical verification. Finally, we had calculated the rate of change of expressway traffic flow characteristics due to visibility and we had come up with a way to apply at capacity and service level analysis.

• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.93-106
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• 2016

This study aimed to estimate and evaluate the thermal mitigation of the urban tree canopy on the summer outdoor environment by quantitative use of mean radiant temperature. This study applied the SOLWEIG model based $T_{mrt}$ comparison method by using both (1) urban tree canopy presence examples and (2) urban tree canopy absence examples as constructed from airborne LiDAR system based three-dimensional point cloud data. As a result, it was found that an urban tree canopy can provide a decrease in the entire domain averaged daily mean $T_{mrt}$ about $5^{\circ}C$ and that the difference can increase up to $33^{\circ}C$ depending both on sun position and site conditions. These results will enhance urban microclimate studies such as indices (e.g., wind speed, humidity, air temperature) and biometeorology (e.g., perceived temperature) and will be used to support forest based public green policy development.

• Journal of the Korean earth science society
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• v.36 no.4
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• pp.330-340
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• 2015

For this study, we developed an algorithm to estimate the total amount of clouds using sky image data from the Skyviewer equipped with CCD camera. Total cloud amount is estimated by removing mask areas of RGB (Red Green Blue) images, classifying images according to frequency distribution of GBR (Green Blue Ratio), and extracting cloud pixels from them by deciding RBR (Red Blue Ratio) threshold. Total cloud amount is also estimated by validity checks after removing sunlight area from those classified cloud pixels. In order to verify the accuracy of the algorithm that estimates total cloud amount, the research analyzed Bias, RMSE, and correlation coefficient compared to records of total cloud amount earned by human observation from the Gangwon Regional Meteorological Administration, which is in the closest vicinity of the observation site. The cases are selected four daily data from 0800 LST to 1700 LST for each season. The results of analysis showed that the Bias in total cloud amount estimated by the Skyviewer was an average of -0.8 tenth, and the RMSE was 1.6 tenths, indicating the difference in total cloud amount within 2 tenths. Also, correlation coefficient was very high, marking an average of over 0.91 in all cases, despite the distance between the two observation sites (about 4 km).

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.393-402
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• 2016

To compensate for limited the satisfaction survey currently conducted by Korea Metrological Administration (KMA), a sentiment analysis via a social networking service (SNS) can be utilized. From 2011 to 2014, with the sentiment analysis, Twitter who had commented 'KMA' had collected, then, using $Na{\ddot{i}}ve$ Bayes classification, we were classified into three sentiments: positive, negative, and neutral sentiments. An additional dictionary was made with morphemes appeared only in the positive, negative, and neutral sentiments of basic $Na{\ddot{i}}ve$ Bayes classification, thus the accuracy of sentiment analysis was improved. As a result, when sentiments were classified with a basic $Na{\ddot{i}}ve$ Bayes classification, the training data were reproduced about 75% accuracy rate. Whereas, when classifying with the additional dictionary, it showed 97% accuracy rate. When using the additional dictionary, sentiments of verification data was classified with about 75% accuracy rate. Lower classification accuracy rate would be improved by not only a qualified dictionary that has increased amount of training data, including diverse keywords related to weather, but continuous update of the dictionary. Meanwhile, contrary to the sentiment analysis based on dictionary definition of individual vocabulary, if sentiments are classified into meaning of sentence, increased rate of negative sentiment and change in satisfaction could be explained. Therefore, the sentiment analysis via SNS would be considered as useful tool for complementing surveys in the future.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.525-535
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• 2020

This study aims to evaluate the economic value of the heat wave watch/warning (HW/W) forecast provided by the KMA (Korea Meteorological Administration) for the public sector. Local govermenments of Korea currently use the HW/W forecasts as a major input variable to determine the preparative requisite level for reducing potential damage by extreme heat events. To assess the value of the HW/W, which is not a marketable commodity, a decision-making model taking into account the cost and loss was established. The 'cost' variable was defined as the heat wave countermeasures budget for Seoul and Busan in 2016, and the 'loss' variable was set as the amount of health insurance claims for those 65 and older obtained from the Health Insurance Review and Assessment Service. Using this model, the value of the HW/W in 2016 was calculated as KRW 4,133M and KRW1,090M for Seoul and Busan, respectively. In addition, if the KMA reduces the False Alarm of the HW/W by a single instance, the value will be increased by KRW 76.6M and KRW 16.8M for the two cities. The results of this study are useful in quantitatively estimation of the value of the HW/W forthe public sector.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.171-179
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• 2015

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.