• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.47-52
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• 2003

Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the LANDSAT TM data was used to detect the change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korea peninsular. Among the several change detection techniques, change vector analysis(CVA), principle component analysis(PCA) and image difference approach are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel values. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood. CVA with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.4-4
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• 2023

C-band SAR 센서를 탑재한 수자원위성은 한반도 수자원 모니터링을 위해 개발되어 2025년 발사가 계획되어 있으며, 수변환경 및 부유물 탐지 및 다양한 활용이 기대되고 있다. 그 중 수변환경은 수변 생태계 안정성을 유지하는 역할을 담당하여 이에 대한 모니터링은 중요하다. s현장 관측 기반 탐지 방법과 비교하여 위성 원격탐사는 광범위한 지역을 반복적으로 관측하여, 연속적인 수변환경 및 부유물 정보를 제공할 수 있다. 이러한 특성에 기반하여 다양한 다중분광 및 SAR (Synthetic Aperture Radar) 위성 원격탐사 자료를 바탕으로 수변환경 및 부유물의 탐지 연구가 이루어졌다. 특히 단일 영상만을 사용하는 기법에 비해 다중분광 및 SAR 영상을 융합하여 높은 정확도를 보인 바 있다. 초기 연구에서는 임계값 알고리즘 또는 현장관측 기반의 부유물 농도와 위성 자료간의 선형관계를 분석하는 단순한 알고리즘이 주를 이루었으나, 최근에는 RF, CNN 등 보다 복잡하고 다양한 인공지능 알고리즘이 적용되어 높은 정확도로 해당 문제들을 해결하고 있다. 본 연구에서는 수자원위성 활용을 위해 인공지능 기반 수변환경 및 부유물 탐지 알고리즘을 개발하고자 한다. 수자원위성의 대체 자료로 유럽우주국의 Sentinel-1 A/B 위성의 C-band SAR 영상을 이용하였으며, 보조자료로 Sentinel-2 다중분광 영상을 이용하였다. 개발된 알고리즘은 수자원 관리를 위한 환경변화 탐지에 유용한 정보로 활용될 수 있을 것으로 기대된다.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1791-1799
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• 2023

The Korea Aerospace Research Institute is responsible for supplying and supporting the utilization of imagery data from the Arirang satellite series for organizations affiliated with the Government Satellite Information Application Consultation. Most of them primarily utilize optical imagery, and there is a relative lack of utilization of Synthetic Aperture Radar (SAR) imagery. In this paper, as part of supporting the use of SAR images, we investigated SAR intensity-based change detection algorithms and their use cases that have been researched to determine SAR intensity-based change detection algorithms to be developed in the future. As a result of the research, we found that various algorithms utilizing intensity difference, correlation coefficients, histograms, or polarimetric information have been researched by numerous researchers to detect and analyze change pixels and the applications of change detection algorithms have been studied in various fields such as a city, flood, forest fire, and vegetation. This study will serve as a reference for the development of SAR change detection algorithms, intended for utilization in the Government Satellite Information Application Consultation.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.870-872
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• 2002

본 연구는 탐지 대상물체의 형상인식이 가능한 비접촉, 원격 탐지장치의 개발에 관한 것이다. 형체인식용 비접촉 시스템은 주로 Magneto- lmpedance법과 Magneto-Inductance법이 있으며, Magneto-Inductance법은 왜곡이 적고, 인체나 탐지 대상물체에 손상을 가져오지 않는다. 본 연구에서는 2극으로 디자인 된 Magnetic Tomography System을 이용하여 물체의 위치에 따른 투자율 변화량을 계산 및 실측하였다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.87-91
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• 2002

본 연구는 탐지 대상물체의 형상인식 이 가능한 비접촉, 원격 탐지장치의 개발에 관한 것이다. 형체인식용 비접촉 시스템은 주로 Magneto-Impedance법과 Magneto-Inductance법이 있 으며, Magneto- Inductance법은 왜곡이 적고, 인체나 탐지대상물체에 손상을 가져오지 않는다. 본 연구에서는 2극으로 디자인 된 Magnetic Tomography System을 이용하여 물체의 위치에 따른 투자율 변화량을 계산 및 실측하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.224-224
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• 2021

광학원격탐사를 통해 취득할 수 있는 초분광 영상은 관련 기술의 발전으로 다양하게 활용이 되고 있다. 특히 초경량 UAV를 기반으로 초분광 센서를 적용한 광학원격탐사는 광범위하게 분포하는 국내 제방의 불안정 요소를 탐지하는데 보다 효과적일 것으로 판단되며 대상에 대한 광역모니터링을 통해 많은 자료를 얻을 수 있고, 고해상도 영상 자료를 활용한 세밀한 분광 및 공간정보 분석이 가능하다. 본 연구에서는 제방 균열 평가를 위해 UAV를 활용하여 안동댐 하류 제방 균열을 대상으로 고해상도 초분광 영상을 취득하였으며, 기 개발된 제방 균열 평가 소프트웨어를 이용하여 조도와 최대강도 데이터에 따른 제방 균열 평가를 실시하였다. 연구지역의 지질은 중생대 백악기의 일직층으로써 적색이암, 셰일, 역질사암 등이 주를 이루고 있으며 제방 내 토양은 대부분 입도가 균일하며 일부 역암이 관찰되는 지역으로 조립토가 주를 이루고 있다. 기 개발된 소프트웨어의 특징은 측정된 데이터를 바탕으로 균열 여부를 판별할 수 있는 프로그램으로써 측정지점마다 별도의 조도와 최대강도 데이터가 주어졌을때, 해당 데이터에 대한 균열 여부를 판별할 수 있다. 주요기능은 제방 균열 여부 판단, 데이터 입력 및 판단을 출력하기 위한 GUI 인터페이스를 제공한다. 연구 결과 제방 균열 평가 소프트웨어를 적용하여 균열과 비균열에 대한 탐지가 가능한 것으로 나타났다. 특히 비균열 포인트의 경우 암석이나 토양의 성질, 빛의 반사에 따라 일부 차이가 있지만 균열은 매우 유사한 반사율 정보를 보이는 것으로 나타났다.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.365-377
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• 2020

Continuous monitoring and immediate response is essential to protect the national maritime territory and maritime resources from the activities of illegal ships. Synthetic Aperture Radar (SAR) images with a wide range of images are effective for maritime surveillance asthe weather and day-night conditions rarely affect to image acquisition. However, an effective ship detection is not easy due to the huge data size of SAR images and various characteristics such as the speckle noise. In this study, the Human Visual Attention System (HVAS) algorithm was applied to KOMPSAT-5 to extract the initial targets, and the SAR-Split algorithm depending on the imaging modes was used to remove false alarms. The detected targets were finally selected by the Constant False Alarm Rate (CFAR) algorithm and matched with the ship's Automatic Identification System (AIS) information. Overall, the detected targets were well matched with AIS data, but some false alarms by ship wakes were observed. The detection rate was about 80% in ES mode and about 64% in ST mode. It is expected that the developed ship detection algorithm will contribute to the construction of a wide area maritime surveillance network.

• The KIPS Transactions:PartC
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• v.19C no.1
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• pp.47-54
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• 2012

Sharing cross-site resources has been adopted by many recent websites in the forms of service-mashup and social network services. In this change, exploitation of the new vulnerabilities increases, which includes inserting malicious codes into the interaction points between clients and services instead of attacking the websites directly. In this paper, we present a system model to identify malicious script codes in the web contents by means of a remote verification while the web contents downloaded from multiple trusted origins are executed in a client's browser space. Our system classifies verification items according to the origin of request based on the information on the service code implementation and stores the verification results into three databases composed of white, gray, and black lists. Through the experimental evaluations, we have confirmed that our system provides clients with increased security by effectively detecting malicious scripts in the mashup web environment.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1363-1372
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• 2021

Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.