• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1331-1339
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• 2023

In support of the National ATM Reformation and Enhancement Plan (NARAE), a trajectory-based aviation weather service is under development through the NARAE-Weather project. Specifically, weather data presented in a standardized digital format facilitates the seamless integration of digital weather data with air traffic information. Thus, this paper introduces an approach that entails structuring numerical model data to integrate aviation weather information and flight trajectory data. The extraction results using structurally transformed data showed superior performance compared to the results extracted from the original data in terms of performance, and this research is poised to enhance the safety and efficiency of airline operations.

• 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.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.61.3-61.3
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• 2021

We, on behalf of the Korean Gemini Office (KGO), introduce three proposal routes besides a standard semester program available for the Korean Gemini users: Fast Turnaround (FT), Director's Discretionary Time (DDT), and Poor Weather (PW). By presenting useful statistics and some examples implemented through these routes, we aim to provide the KAS members insights how well these observing routes have been utilized by the Gemini partners. Finally, we provide several useful suggestions to the KAS community for preparing these programs.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.38.2-38.2
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• 2021

We, on behalf of Korean Gemini Office (KGO), present the comprehensive knowledge on the Gemini Band 3 program and introduce KGO's activities to promote research of Korean community utilizing Band 3 programs. We first describe the role and realities of Band 3 programs in comparison with Band 1 and 2. Then, we will provide useful suggestions for preparing Band 3 programs and introduce a few selected cases that successfully use the Band 3 time. In addition to Band 3, we will briefly summarize other proposal opportunities including the Fast Turnaround and Poor Weather Proposals.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.269-269
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• 2019

첨단장비 및 기술의 도입으로 수문조사 측정기술 수준은 일정수준에 도달하였으나, 여전히 수문조사 시 많은 인력과 시간이 요구되고 있다. 수문조사 업무 규모와 범위에 비해 현재 수문조사에 투입되는 인력은 지극히 제한적이기 때문에 측정기술 자체보다는 운영 인프라 및 환경적 개선이 필요하다고 할 수 있다. 또한 유량 측정시 정확한 첨두유량 발생시각을 포착하기 어려울 뿐만아니라, 때로는 위험이 수반되기 때문에 업무의 비효율성 및 관측 자료의 정확도가 저하되는 문제가 발생하고 있다. 본 연구에서는 비교적 높은 시간 정확도를 가지는 레이더 자료와 예측자료를 이용하여 실시간(또는 시간단위)으로 제공되는 기상정보(호우 예상지점, 도달시간 등)를 활용하여 현 조사원의 위치, 조사원의 구역 내에서 측정 우선 지점(주요 예보 지점), 측정 지점까지의 이동시간 등을 고려하여 유량 측정 순서, 최적 경로를 탐색하고자 한다. 실시간(또는 시간단위) 기상상황과 이에 따른 조사원의 이동 순서, 경로를 디지털화하여 표출(시스템, 모바일 App. 등)하여 제공함으로써 조사수행 인력의 이동을 최소화하고 효율적인 수문조사를 위한 정보 제공할 수 있을 것으로 사료되며 또한 관리자 입장에서 표출시스템의 정보를 통해 실시간 현장 정보 파악함으로써 가변하는 기상상황과 현장의 환경적 변화 사이에서 유연한 대처 및 유동적인 지원을 가능케 할 수 있을 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.