• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.455-464
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• 2009

Lee(2009) proposed the boundary-adaptive despeckling method using a Bayesian model which is based on the lognormal distribution for image intensity and a Markov random field(MRF) for image texture. This method employs the Point-Jacobian iteration to obtain a maximum a posteriori(MAP) estimate of despeckled imagery. The boundary-adaptive algorithm is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The boundary-adaptive scheme was comprehensively evaluated using simulation data and the effectiveness of boundary adaption was proved in Lee(2009). This study, as an extension of Lee(2009), has suggested a modified iteration algorithm of MAP estimation to enhance computational efficiency and to combine classification. The experiment of simulation data shows that the boundary-adaption results in yielding clear boundary as well as reducing error in classification. The boundary-adaptive scheme has also been applied to high resolution Terra-SAR data acquired from the west coast of Youngjong-do, and the results imply that it can improve analytical accuracy in SAR application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.447-454
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• 2013

The geolocation accuracy of SAR satellite imagery is affected by orbit and sensor information and external variables such as DEM accuracy and atmospheric delay. To predict geolocation accuracy of KOMPSAT-5 and KOMPSAT-6, this paper uses TerraSAR-X imagery which has similar spec. Simulation data for sensitivity analysis are generated using range equation and doppler equation with several key error sources. As a result of simulation analysis, the effect of sensor information error is larger than orbit information error. Especially, onboard electronic delay needs to be monitored periodically because this error affects geolocation accuracy of slant range direction by 30m. Additionally, DEM accuracy causes geolocation error by 20~30m in mountainous area and atmospheric delay can occur by 5m in response to atmospheric condition and incidence angle.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1777-1788
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• 2022

The reservoir is a major water supply source in the domestic agricultural environment, and the monitoring of water storage of reservoirs is important for the utilization and management of agricultural water resource. Remote sensing via satellite imagery can be an effective method for regular monitoring of widely distributed objects such as reservoirs, and in this study, image classification and image segmentation algorithms are applied to Sentinel-1 Synthetic Aperture Radar (SAR) imagery for water body detection in 53 reservoirs in South Korea. Six algorithms are used: Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), Otsu, Watershed (WS), and Chan-Vese (CV), and the results of water body detection are evaluated with in-situ images taken by drones. The correlations between the in-situ water surface area and detected water surface area from each algorithm are NN 0.9941, SVM 0.9942, RF 0.9940, Otsu 0.9922, WS 0.9709, and CV 0.9736, and the larger the scale of reservoir, the higher the linear correlation was. WS showed low recall due to the undetected water bodies, and NN, SVM, and RF showed low precision due to over-detection. For water body detection through SAR imagery, we found that aquatic plants and artificial structures can be the error factors causing undetection of water body.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1D
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• pp.89-94
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• 2012

The RFM (Rational Function Model), as an alternative to physical sensor models has been widely used for photogrammetric processing of high resolution optical satellite imagery. However, the application of RF modeling to the SAR (Synthetic Aperture Radar) is very limited. In this paper, stereo radargrammetric processing of TerraSAR-X stereo pairs with RFM is implemented and analyzed. The investigation has shown that the accuracy of TerraSAR-X DSM is similar to that of the commercial S/W product. Finally, it is demonstrated that RFM is effective and feasible in the application to the radargrammetric SAR image processing.

• The Journal of the Korea Contents Association
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• v.7 no.3
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• pp.176-186
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• 2007

As SAR data have the strong point that is not influenced by weather or light amount in comparison with optical sensor data, they are highly useful for temporary analysis and can be collected in time of unforeseen circumstances like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. As a result of analyzing the extracted coherence and interferogram images, it was shown that the DInSAR 3-pass method produces more suitable coherence values than the InSAR method. The accuracies of DEM extracted from the SAR data were evaluated by employing the DEM derived from the digital topographic maps of 1:5000 scale as reference data. And it was ascertained that baselines between antenna locations largely affect the accuracy of extracted DEM.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.310-315
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• 1999

We extracted narrow open water streams from JERS-1 SAR images of the Amazon rain forest. The extracted range of these streams were almost comparable to a high level extraction of the same streams from near-IR images of JERS-1 VNIR data notwithstanding that these features in SAR images show the strong dependence of the observation angle. Large water bodies are relatively easy to extract from JERS-1 SAR images, as they tend to appear as very dark areas; but streams whose width is nearly equal to or less than the spatial resolution no longer appear as very dark features. By using strong scatterers distributed sparsely along the radar facing sides of the streams, we can successfully estimate approximate ranges of waterways and then extract relatively dark line-like features within these ranges.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.159-159
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• 2017

효율적인 물 관리를 위해서는 하천 유량 파악이 필수적이지만, 경제적 이유 등으로 인하여 현장에서 정확한 유량 자료를 꾸준히 확보하는 데에는 한계가 있다. 본 연구에서는 이러한 문제점을 극복하고자 SAR 영상을 이용하여 하천의 수위와 유량을 추정하였다. SAR 영상 자료는 악천후 및 주야의 영향을 받지 않는 ESA(European Space Agency)의 Sentinel-1 영상을 이용하였다. 위성자료에서 하천의 면적을 추출한 후 수위 및 유량과의 상관관계를 분석하였다. 촬영 시간 등에 의한 위성 영상의 조도 차이에 따른 하천 면적의 오차를 제거하기 위하여 영상을 보정하였고 주변 지역에 의한 오차를 줄이기 위하여 하천유역을 분리하여 면적을 추출하였다. 이를 통해 하천 면적과 수위 및 유량의 상관관계를 파악하였다. 국내 10여 개의 하천에 대하여 기법을 적용한 결과, 수위와 유량을 비교적 정확히 추정할 수 있었다. 본 연구의 결과는 미계측 유역의 수자원 관리 능력을 향상시킬 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.313-313
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• 2018

유량 자료는 수자원 계획 및 개발, 정책결정, 관련 시설 운영 등의 가장 기초가 되는 핵심 자료이다. 하지만 전세계적으로 많은 유역에서 경제적 이유 등으로 인해 현장에서 정확한 유량 자료를 확보하는데 한계가 있다. 본 연구에서는 이러한 문제점을 극복하고자 SAR 영상을 활용한 하천의 유량 추정 기법을 개발하였다. 악천후 및 주야의 영향을 받지 않는 SAR 영상 자료인 유럽항공우주국 ESA(European Space Agency)의 Sentinel-1 영상자료와 함께 한강홍수통제소에서 제공하는 지상 관측 자료를 사용하여, 위성 영상자료에서 하천의 면적을 추출한 후 유량과의 상관관계를 분석하였다. 촬영 시간 등에 의한 위성 영상의 조도 차이에 따른 하천 면적의 오차를 제거하기 위하여 각 관측소별로 영상을 보정하였고 주변 지역에 의한 오차를 줄이기 위하여 하천유역을 분리하여 면적을 추출하였다. 이를 통해 하천 면적과 유량의 상관관계를 파악하였다. 국내 10여 개의 하천에 대하여 기법을 적용한 결과, 유량을 비교적 정확히 추정할 수 있었다. 본 연구의 결과는 미계측 유역의 수자원 관리 능력을 향상시킬 것으로 기대된다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.1-7
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• 1998

SAR data can be achieved independently of weather conditions or sun illumination which is main limitation of electro-optical sensor to get image. The information from imagery can be more enlarged using Shh data be-cause SAR data offers different information from electro-optical sensor. SAR data contains various distortions caused by the radar specification and geometric properties of data acquisition. These distortions should be removed to get the information with acceptable accuracy. In this study, we aimed to correct the radiometric distortion in Shh image caused by the geometric property of the object. For this purpose, we simulated the SAR image by modelling of the power of return beam which is variable according to the geometric configuration between SAR antenna and ground object. Dividing the SAR image by the simulation image, then, we can get the radiometrically corrected image. As a result of this study, we could minimize the effect of radiometric distortion in achieving some qualitative information from SAR image for the related field, such as Geospatial Information System.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.1-15
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• 1994

Since Seasat SAR mission in 1978, SAR has become one of the most important surface imaging tools in satellite remote sensing SAR achieves high resolution by signal processing synthesizing a larger aperture. Therefore, SAR signal processing along with antenna technology has been centered upon SAR technologies. Thus interpreters of SAR imagery as well as those who involved in signal processing require the knowledge of the principal SAR processing algorithm. Although the conventional range-Doppler approach has been widely adopted by many SAR processors, azimuth compression including the range migration has been problematic. The recent development of the wavenumber domain approace is able to provide high precision SAR focusing algorithm. Compared with the wavenumber domain algorithm derived by applying Born (first) approximation, the transfer function of the conventional range-Doppler algorithm accounts only for the first order approximation of the exact transfer function. The results of a simulation and an actual test using airborne C-band SAR configuration demonstrate the dxcellent performance of the wavenumber domain algorithm.