• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.201-204
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• 2006

태풍의 경우, 주요 자연재해 중의 하나로 태풍의 상황을 정확하게 파악하는 것은 기상예측의 정도를 높이고, 재해를 방지하는데 중요한 역할을 할 수 있다. 일반적으로 태풍의 동향을 감시하는데 있어, MTSAT 등의 기상위성이 주로 활용되고 있다. 근년 인공위성의 원격탐사를 이용하여 광범위의 해양에 대한 해상풍과 파랑의 관측이 가능하게 되었다. 본 연구에서는, 2000년 QuickSCAT위성에 의한 해상풍의 월변동 특성을 조사하고, 7월에 한반도에 영향을 준 태풍 카이탁내의 해상풍을 검토하였다. 추가로 2005 년 8월 30일의 태풍 탈림에 대해서 ENVISAT ASAR Scan SAR에 의한 해상풍 추출을 시도하였다. QuickSCAT 에 의한 풍향을 이용한 방법과 SAR 자체의 패턴을 이용한 방법이 비교되었다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.401-404
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• 2007

Augustine volcano is an active stratovolcano located at the southwest of Anchorage, Alaska. Augustine volcano had experienced seven significantly explosive eruptions in 1812, 1883, 1908, 1935, 1963, 1976, and 1986, and a minor eruption in January 2006. We measured the surface displacements of the volcano by radar interferometry and GPS before and after the eruption in 2006. ERS-1/2, RADARSAT-1 and ENVISAT SAR data were used for the study. Multiple interferograms were stacked to reduce artifacts caused by different atmospheric conditions. Least square (LS) method was used to reduce atmospheric artifacts. Singular value decomposition (SVD) method was applied for retrieval of time sequential deformations. The observed surface displacements from satellite radar interferometry were compared with GPS data. Satellite radar interferometry helps to understand the surface displacements system of Augustine volcano.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.143-146
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• 2009

다산기지 주변 해역인 스발바드섬은 북반구 해빙 분포지역의 가장자리에 위치해 있으며 해빙의 이동이 비교적 빠른 지역이다. 지구 온난화의 영향을 받는 대표적인 지역으로 이 지역의 해빙변화에 대한 연구는 지구온난화의 지표로서 중요성을 가진다. 스발바드섬 주변의 해빙에서 얻어진 다편파 SAR 데이터를 분석하여 해빙에 대한 후방산란계수의 특성을 분석하고자 한다. 데이터 획득에는 ENVISAT/ASAR (2002 년 발사 C-밴드, 다편파 사용)과 PALSAR (2006 년 발사, L-밴드, 다편파 사용)의 두 가지 SAR 가 이용되었으며 데이터 획득 시기는 해빙의 변화가 활발한 4 월경이다. 기본적으로 L-밴드와 C-밴드의 두 가지 밴드별 차이에 관한 특성을 알아보고 기타 후방산란계수에 영향을 주는 요소들에 대하여 알아보고자 한다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.266-269
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• 2007

This paper reports the preliminary results on the study of radargrammetry especially for a high-resolution satellite synthetic aperture radar system. Theoretical configurations for radargrammetry in terms of coverage, orbit selection, incidence angles, height sensitivity of parallax and height resolution of DEM were calculated according to the proposed orbit characteristics and the imaging modes of KOMPSAT-5 SAR. Possible imaging strategies and mission scenarios for coverage versus rapidity are suggested for a future mission dedicated to radargrammetry.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.2
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• pp.163-168
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• 2008

Ship detection from satellite remote sensing is a crucial application for global monitoring for the purpose of protecting the marine environment and ensuring marine security. It permits to monitor sea traffic including fisheries, and to associate ships with oil discharge. An automatic ship detection approach for RADARSAT Fine Synthetic Aperture Radar (SAR) image is described and assessed using in situ ship validation information collected during field experiments conducted on August 6, 2004. Ship detection algorithms developed here consist of five stages: calibration, land masking, prescreening, point positioning, and discrimination. The fine image was acquired of Ulsan Port, located in southeast Korea, and during the acquisition, wind speeds between 0 m/s and 0.4 m/s were reported. The detection approach is applied to anchoring ships in the anchorage area of the port and its results are compared with validation data based on Vessel Traffic Service (VTS) radar. Our analysis for anchoring ships, above 68 m in length (LOA), indicates a 100% ship detection rate for the RADARSAT single beam mode. It is shown that the ship detection performance of SAR for smaller ships like barge could be higher than the land-based radar. The proposed method is also applied to estimate the ship's dimensions of length and breadth from SAR radar cross section(RCS), but those values were comparatively higher than the actual sizes because of layover and shadow effects of SAR.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.663-668
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• 2008

Recently, World Radio Conference(WRC)-2007 approved the ultrawide bandwidth of 500 MHz for the use of spaceborne synthetic aperture radar in X-band for the EESS(Earth Exploration Satellite Service) in order to improve the SAR imaging resolution. It is concerned about the interference impact from the spaceborne SAR that may cause to most of ground radars due to the extended ultra wideband. In this paper, in order to predict the interference impact of the ground-based radar from the spaceborne radar, radar interference model is presented using radar characteristic parameters by taking into account the operating environments of the spaceborne and ground based radar in the time, space, and spectrum domains. Using the spaceborne SAR model of TerraSAR-X and ground radar model of meteorological radar recommended by ITU-R, the interference impact was assessed through the computer simulation to see the possible interference impact of the ground based radar operating in the Korean peninsula.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.365-374
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• 2017

SAR (Synthetic Aperture Radar) is an effective tool for monitoring areas damaged by disasters. Full PolSAR (Polarimetric SAR) enhances SAR's capabilities by providing specific scattering mechanisms. Thus, full PolSAR data have been widely used to analyze the situation when disasters occur. To interpret full PolSAR data, model-based decomposition methods are frequently used due to its easy physical interpretation of PolSAR data and computational efficiency. However, these methods present problems. One of the key problems is the overestimation of the volume scattering component. To minimize the volume scattering component, the OA (Orientation Angle) compensation method is widely utilized. This paper shows that the effect of the OA compensation was analyzed over landslide affected areas. In this paper, the OA compensation is applied by using the OA estimated from the maximum relative Hellinger distance. We conducted an experiment using two full polarimetric ALOS/PALSAR (Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar)-2 data collected over Mocoa, Colombia which was seriously damaged by the 2017 Mocoa landslide. After OA compensation, the experimental results showed volume scattering power decreased, while the double-bounce and surface scattering power increased. Particularly, significant changes were noted in urban areas. In addition, after OA compensation, the separability of the double-bounce and surface scattering components are improved over the damaged building areas. Furthermore, changes in the OA can discriminate visually between the damaged building areas and undamaged areas. In conclusion, we demonstrated that the effect of OA compensation improved the influence of the double-bounce and surface scattering components, and OA changes can be useful for detecting damaged building areas.