• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.28-28
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• 2017

최근 기후변화로 인하여 국지성 집중호우 및 태풍으로 인한 피해가 빈번하게 발생하고 있으며, 산지가 많은 국내에서는 토석류 피해 또한 급증하고 있다. 2011년 집중호우로 인해 서울시에 위치한 우면산에서 많은 토석류가 발생하였고 이로 인해 많은 인명과 재산피해가 발생하였다. 여기서, 토석류란 산악지역의 상류에서 유발된 강우와 함께 토석 및 유목 등이 섞여 계곡하류로 빠르게 이동하는 현상을 의미한다. 이러한 토석류의 피해를 줄이기 위해서는 발생가능성과 범위를 예측하는 것이 무엇보다 중요하며, 토석류 발생에 영향을 미치는 가장 큰 두 가지 원인은 강우와 지형학적인 조건이라고 할 수 있다. 그러나, 현실적으로 강우정보는 하류지역에 위치하고 있는 AWS 기상관측소의 정보만을 이용 할 수 있기 때문에 산악지역에서 시시각각 변화하는 강우정보를 얻는 데는 한계가 있다. 그러므로 시 공간적인 강우의 변동성을 관측할 수 있는 레이더 강우정보를 이용하는 것은 매우 중요하다고 판단된다. 따라서 본 연구에서는 시 공간적으로 우수한 해상도를 가진 레이더 강우 정보와 토석류 2차원 수치해석 모형인 RAMMS(Rapid Mass Move Simulation)모형을 연계하여 토석류 모의를 실시하여 토석류의 유동심, 토석유속, 충격력 등을 산정하였고, 지상강우정보를 이용하여 산정된 결과와 비교함으로서 레이더 강우정보를 이용한 토석류 예측의 적용 가능성을 확인하였다.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.321-334
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• 2006

The need for economical and accurate presentations of equivalent radar reflectivity( $Z_e$) data in an orthogonal coordinate system has existed for some time. So, in this study, a fast and efficient procedure has been developed which allows the systematic interpolation of digital reflectivity data from radar space into Cartesian space. At first, QC(Quality Control) of radar data has been executed for extracting uncontaminated Constant Altitude Plan Position Indicator(CAPPI) data. The algorithm is designed so that only one ordered pass through the original Plan Position Indicator(PPI) scan data is necessary to complete the interpolation process. The model can calculate various resolution and altitude reflectivity data for many kinds of hydrological usage.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.4-6
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• 2022

전국 23개소에 설치되어 운영중인 해상교통관제시스템(Vessel Traffic System, VTS)의 관제 데이터 실시간 공유를 위해 클라우드 신기술을 적용한 통합 플랫폼을 개발하고 있으며, 이를 위해서는 관제 데이터의 수집, 처리, 분석에서부터 관제 운영 절차에 이르는 전 분야에 대한 새로운 정의가 필요하다. 본 논문에서는 클라우드 기반 차세대 VTS 통합 플랫폼에 대한 다양한 분야에서의 설계를 제시하고자 한다.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.1-15
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• 2017

Information on radar rainfall with high spatio-temporal resolution over large areas has been used to mitigate climate-related disasters such as flash floods. On the other hand, a well-known problem associated with the radar rainfall using the Marshall-Palmer relationship is the underestimation. In this study, we develop a new bias correction scheme based on the quantile regression method. This study employed a bivariate copula function method for the joint simulation between radar and ground gauge rainfall data to better characterize the error distribution. The proposed quantile regression based bias corrected rainfall showed a good agreement with that of observed. Moreover, the results of our case studies suggest that the copula function approach was useful to functionalize the error distribution of radar rainfall in an effective way.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.445-458
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• 2008

Image chain analysis of synthetic aperture radar (SAR) satellite is one of the primary activities for satellite design because SAR image quality depends on spacecraft bus performance as well as SAR payload. Especially, satellite pointing and stability error make worst effect on the original SAR image quality which is implemented by SAR payload design. In this research, Image chain analysis S/W was developed in order to analyze the SAR image quality degradation due to satellite pointing and stability error. This S/W consists of orbit model, attitude control model, SAR payload model, clutter model, and SAR processor. SAR raw data, which includes total 25 point targets in the scene of $5km{\times}5km$ swath width, was generated and then processed for analysis. High resolution mode (spotlight), of which resolution is 1m, was applied. The results of image chain analysis show that radiometric accuracy is the most degraded due to the pointing error. Therefore, the successful design of attitude control subsystem in spacecraft bus for enhancing the pointing accuracy is most important for image quality.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.277-277
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• 2023

최근 기후변화의 영향으로 호우의 발생빈도가 증가하고 있는 추세이며, 도시지역의 호우는 돌발적이고 국지적인 특성을 가지고 있어 인명과 재산피해 역시 증가하고 있으며, 급격한 도시화로 인한 구조적으로 홍수에 취약한 실정이다. 국지성 도시호우는 저층(1 km 내외)에서 형성되는 강우가 지배적이며, 기존의 대형레이더는 높은 산 정상에 설치되어 1.5 km 이상의 강우관측을 중심으로 운영됨에 따라 저층강우의 탐지 및 변동성 관측에 취약하여, 이에 대형 레이더에서 뿐만 아니라 도시단위의 국지성 호우관측에 대응할 수 있는 소형 레이더 기반 고정밀 강우관측 마련 및 운영 기술이 필요하다. 현재 K-water는 부산 에코델타 스마트시티에 도시 물재해 플랫폼 구현의 일환으로 돌발강우사전 탐지 및 도시의 신속·정확한 강우 관측을 위하여 높은 시공간 해상도를 제공하는 이중편파X 밴드 소형 강우레이더를 설치하고, 효율적 운용을 위해 각 고도각에서의 빔 차폐율을 확인하고 이를 고려한 최적 관측전략을 수립하였다. 또한 Z-Phi 방법을 이용한 반사도 감쇠 보정 기술을 개발하였으며, 강우 추정을 위해 하이브리드 고도면 합성 기법(HSR) 기법을 적용하고 검증하였다. 이후 소형 레이더의 정량적 추정강수를 이용하여 강우예측 정보를 생산하기 위해 이류모델을 적용하고, 비슬산과 소형 합성 레이더 추정강수로 선행 10분에서 180분까지 예측할 수 있도록 개발하였다. 또한, 지상강우관측 자료와의 정확도 비교 평가를 수행하고, 행정구역 및 표준유역의 예측 평균강우량을 생산하여 부산 에코델타 스마트시티 도시 물재해 통합관리 시스템과 연계운영을 위한 후속 과업을 수행중에 있다.

• Aerospace Engineering and Technology
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• v.2 no.1
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• pp.63-72
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• 2003

On the basis of sensor types, satellites can be classified by two types, which are optical observation satellite and radar observation satellite. A satellite type is selected according to the specific mission. Optical observation satellite is more appropriate for getting high geometric resolution images and radar observation satellite is more appropriate for getting images independent of weather condition the more a demand of satellite increases, the more an importance of information increases. Therefore, development trend and state of earth observation satellite are surveyed and described in this paper. In the future, domestic development of satellites will be planned considering trend of satellite technologies.

• Journal of the Korean Geotechnical Society
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• v.29 no.9
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• pp.17-29
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• 2013

The geophysical methods have an advantage for investigating the wide area with low cost, and thus the application of these methods has been increased. The objective of this paper estimates the characteristics of alluvium through the geophysical methods including elastic wave, electrical resistivity and ground penetration radar. And the standard penetration test is also carried out for verifying the geophysical data with comparison. The sources of elastic wave method are divided into hammer and sissy and the electrical resistivity method is applied with different sizes, shapes and arrays of electrode for deciding the effective way. The center frequency is determined to be 270 MHz for considering the characteristics of soil. The results of ground penetration radar are also compared with those of standard penetration test. The high resolution shows when the source is a sissy in elastic wave method, however, the water level is not identified. In the electrical resistivity method, the non-polarizable electrode and schlumberger array show highly reliable data and the resolution of ground penetration radar is low. Thus, the results of this study are widely applied for determining the appropriate method when investigating the characteristics of alluvium.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1329-1338
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• 2021

Rain radar provides high spatio-temporal radar rainfall that can be used as input data to short-term precipitation forecasting models. Korea Institute of Civil Engineering and Building Technology (KICT) has developed a flash flood forecasting system that is providing flash flood forecasting based on short-term rainfall forecasts estimated by the radar rainfall. Accuracy of the radar rainfall as well as the short-term rainfall forecasts, however, can deteriorate when radar polarimetric variables have error. In this study, we develope real-time program that can correct the error inherent in the radar polarimetric variables. First, effect according to the correction of the error was verified using 363 rainfall events on non real-time. The accuracy (1-NE) of the radar rainfall was approximately 70% and correlation coefficient was higher than 0.8 after correcting the error on non real-time. The accuracy (1-NE) using the real-time program was also approximately 70% after correcting the error.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.43-52
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• 2016

Due to the characteristics of microwave signals, Radar satellite image has been used for flood detection without weather and time influence. The more methods of flood detection were developed, the more detection rate of flood area has been increased. Since flood causes a lot of damages, flooded area should be distinguished from non flooded area. Also, the detection of flood area should be accurate. Therefore, not only image resolution but also the filtering process is critical to minimize resolution degradation. Although a resolution of radar images become better as technology develops, there were a limited focused on a highly suitable filtering methods for flood detection. Thus, the purpose of this study is to find out the most appropriate filtering method for flood detection by comparing three filtering methods: Lee filter, Frost filter and NL-means filter. Therefore, to compare the filters to detect floods, each filters are applied to the radar image. Comparison was drawn among filtered images. Then, the flood map, results of filtered images are compared in that order. As a result, Frost and NL-means filter are more effective in removing the speckle noise compared to Lee filter. In case of Frost filter, resolution degradation occurred severly during removal of the noise. In case of NL-means filter, shadow effect which could be one of the main reasons that causes false detection were not eliminated comparing to other filters. Nevertheless, result of NL-means filter shows the best detection rate because the number of shadow pixels is relatively low in entire image. Kappa coefficient is scored 0.81 for NL-means filtered image and 0.55, 0.64 and 0.74 follows for non filtered image, Lee filtered image and Frost filtered image respectively. Also, in the process of NL-means filter, speckle noise could be removed without resolution degradation. Accordingly, flooded area could be distinguished effectively from other area in NL-means filtered image.