• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.389-395
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• 2014

This technical note describes about the base stages of technology implementation for establishing "Early Warning System for Weather Hazard Management in Climate-smart Agriculture" to national onsite service. First of all, a special weather report service at catchment was represented sequential risk of 810 units of catchment by spatial statistical methods to existing 150 counties units special weather report released in KMA. The second, chronic hazard alarm service based on daily data of 76 Synoptic stations was monitor about 810 Catchment of mid-long term lapse weather and represented as a relative risk index chronic hazard risk of this time in preparation for the climatological normal conditions in the same period. Finally, we establish the foundation for delivering individually calculated field specific in hazard risk about volunteer farmer of early warning service demonstration area in seomjin downstream watershed. These three types of information were built a near real-time map service on the VWORLD background map of Ministry of Land as superposed layers nationwide catchment and demonstration areas within the farm unit weather hazard.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.55-60
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• 2015

Agro-Meteorological Information Service (AMIS) network has been established since 2001 by Rural Development Administration (RDA) in Korea, and has provided access to current and historical weather data with useful information for agricultural activities. AMIS network includes 158 automated weather stations located mostly in farm region, with planning to increase by 200 stations until 2017. Agrometeorological information is disseminated via the web site (http://weather.rda.go.kr) to growers, researchers, and extension service officials. Our services will give enhanced information from observation data (temperature, precipitation, etc.) to application information, such as drought index, agro-climatic map, and early warning service. AMIS network of RDA will help the implementation of an early warning service for weather risk management.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.257-258
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• 2015

The amount of damages caused by natural hazards is consistently growing due to the unusual weather and extreme events. At the same time, property damage by natural hazards is rapidly increasing as well. Hence, we need systematic anti-disaster activities and consulting that can react to such a situation. To address these needs, we investigated and analyzed insured claim payouts from natural hazards by administrative area, and calculate the risk index utilizing GIS. According to the index, this map is identifying the areas of greatest natural hazard risk. The ranking of natural disaster vulnerability based on the risk index, and risk grades were divided into five based on the ranking. This map integrates the natural hazard losses to assist in comprehensive and effective loss prevention activities using analysis of regional loss claims from natural hazards. Moreover, this map can be as utilized as loss mitigation and prevention activities to verify the distribution of exposure and hazards.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.43-54
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• 2018

Images taken in haze weather are characteristic of low contrast and poor visibility. The process of reconstructing clear-weather image from a hazy image is called dehazing. The main challenge of image dehazing is to estimate the transmission map or depth map for an input hazy image. In this paper, we propose a single image dehazing method by utilizing the Generative Adversarial Network(GAN) for accurate depth map estimation. The proposed GAN model is trained to learn a nonlinear mapping between the input hazy image and corresponding depth map. With the trained model, first the depth map of the input hazy image is estimated and used to compute the transmission map. Then a guided filter is utilized to preserve the important edge information of the hazy image, thus obtaining a refined transmission map. Finally, the haze-free image is recovered via atmospheric scattering model. Although the proposed GAN model is trained on synthetic indoor images, it can be applied to real hazy images. The experimental results demonstrate that the proposed method achieves superior dehazing results against the state-of-the-art algorithms on both the real hazy images and the synthetic hazy images, in terms of quantitative performance and visual performance.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.599-608
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• 2018

As natural disasters are increasing due to the unusual weather and the modern society is getting complicated, the rapid change of the urban environment has increased human disasters. Thus, citizens are becoming more anxious about social safety. The importance of preparation for safety has been suggested by providing the disaster safety services such as regional safety index, life safety map, and disaster safety portal application. In this paper, we propose an application framework to predict the urban safety index based on user's location with realtime weather/atmosphere data after creating a predication model based on the machine learning using number of occurrence cases and weather/atmosphere history data. Also, we implement an application to provide traffic safety index with executing preprocessing occurrence cases of traffic and weather/atmosphere data. The existing regional safety index, which is displayed on the Si-gun-gu area, has been mainly utilized to establish safety plans for districts vulnerable to national policies on safety. The proposed system has an advantage to service useful information to citizens by providing urban safety index based on location of interests and current position with realtime related data.

• Atmosphere
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• v.25 no.2
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• pp.339-351
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• 2015

The purpose of this study is for the fundamental understandings about building morphological parameters and aerodynamic roughness parameters of Seoul, Korea using the detailed urban geographic information datasets. Applied roughness parameter calculations are based on a digital map of buildings with lot area polygons. The quality of the developed roughness length ($z_0$) of Seoul was evaluated with densely installed 107 automatic weather stations. The correlation coefficient results between averaged wind speeds of AWS data and averaged $z_0$ is -0.303 in night and -0.398 in day (200 m radii circles case). Further $z_0$ enhancement should follow by considering other surface features such as high tree and orography of Seoul. However, this study would meet the needs to for local- or meso-scale meteorological modeling applications of Seoul. However, further studies would require for enhancing the $z_0$ applications of Seoul.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.48-60
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• 2021

Following the global air-traffic market growth outlook, urgency of technical development is needed in responding to changes in the international air-traffic management paradigm and to prepare technology securing and spreading strategies, which are consistent with systematic aviation weather service policies and evolution direction. Although air traffic has decreased significantly due to COVID-19, normalcy is expected from 2024, as announced by IATA. According to the future air transportation market outlook and development trends of related technologies, Korea has established and implementing the next-generation air transportation system construction plan(NARAE) to secure international competitiveness and leadership in the future. Therefore, this paper describes the technical, economic background and requirements of numerical model-based aviation weather R&D projects for successful implementation of domestic NARAE plans and providing aviation safety and air traffic service efficiency. Furthermore, we proposed numerical-model-based technology development content, strategies and detailed load-map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.397-405
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• 2015

Currently, Korea's digital maps are being produced through traditional aerial photogrammetry methods. Aerial photogrammetry is the most economical way to produce a map of a wide area. However, timely survey is not allowed depends on weather condition and it is inefficient for small area surveying in economic point of view. Therefore, it costs too much and needs long time to produce a map for various small areas where are terrestrial changes for updating the map. In contrast, UAV photogrammetry is possible to work even in cloudy weather because of shooting at low altitude below the clouds. It also has excellent mobility and shoot quickly and well suited for small-scale mapping in several places by low cost. In this study, we produced an ortho-photo and digital map with the UAV photogrammetry method using SIFT and SfM algorithm and verified its accuracy to evaluate the applicability for future digital map updates. The accuracy was verified by comparing the results of the ground survey for check points selected on the digital map. Test results show small errors at ±2.6cm in X coordinates, ±2.8cm in Y coordinates and ±5.8cm in height and we could find a possibility that UAV photogrammetry would be fully applicable for digital map updating.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.545-548
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• 2002

선박의 안전한 항해를 위해서 필수 장비 중 하나인 기상 팩스 장비는 연안국에서 FSK 방식으로 변조된 무선 주파수를 통해서 보내는 기상도를 선박에서 수신하여 이미지화 하는 장비이다. 연안국에서는 기상도를 스캔 한 후에 중심 주파수를 1900Hz로 하고, 흑점을 1500Hz, 백점을 2300Hz 신호로 FSK 변조하여 방송하면 선박에서 이 신호를 수신한다. 따라서 현재는 기상 팩스를 받기 위해서는 기상 팩스 장비가 필요하다. 본 논문에서는 선박에 일반적으로 설치되어 있는 IBM-PC를 이용하여 소프트웨어만을 사용하여 기존의 기상 팩스 장비가 가지고 있는 모든 기능을 구현하고, 기상도의 출력, 편집, 저장 기능을 추가로 설계 및 구현하였다. IBM-PC에서는 RS-232C 보트를 통해 수신된 신호를 Timer Interrupt와 Serial Interrupt를 사용하여 이미지화 하고 주파수를 선택할 수 있게 하고, 실시간 처리 등을 소프트웨어적으로 가능하게 하였다. IBM-PC를 사용함으로 기상도의 수신 및 상태를 개선하는 이미지의 보정이 가능하며, 저장 후 처리가 용이하고, 별도의 기상 팩스 장비를 구입할 필요가 없는 경제적인 기상 팩스 시스템이다.

• The Plant Pathology Journal
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• v.26 no.1
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• pp.37-48
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• 2010

This paper describes a web-based information system for plant disease forecast that was developed for crop growers in Gyeonggi-do, Korea. The system generates hourly or daily warnings at the spatial resolution of $240\;m{\times}240\;m$ based on weather data. The system consists of four components including weather data acquisition system, job process system, data storage system, and web service system. The spatial resolution of disease forecast is high enough to estimate daily or hourly infection risks of individual farms, so that farmers can use the forecast information practically in determining if and when fungicides are to be sprayed to control diseases. Currently, forecasting models for blast, sheath blight, and grain rot of rice, and scab and rust of pear are available for the system. As for the spatial interpolation of weather data, the interpolated temperature and relative humidity showed high accuracy as compared with the observed data at the same locations. However, the spatial interpolation of rainfall and leaf wetness events needs to be improved. For rice blast forecasting, 44.5% of infection warnings based on the observed weather data were correctly estimated when the disease forecast was made based on the interpolated weather data. The low accuracy in disease forecast based on the interpolated weather data was mainly due to the failure in estimating leaf wetness events.