• Title/Summary/Keyword: SAR satellite image

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Analysis of Image Integration Methods for Applying of Multiresolution Satellite Images (다중 위성영상 활용을 위한 영상 통합 기법 분석)

  • Lee Jee Kee;Han Dong Seok
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.4
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    • pp.359-365
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    • 2004
  • Data integration techniques are becoming increasing1y important for conquering a limitation with a single data. Image fusion which improves the spatial and spectral resolution from a set of images with difffrent spatial and spectral resolutions, and image registration which matches two images so that corresponding coordinate points in the two images correspond to the same physical region of the scene being imaged have been researched. In this paper, we compared with six image fusion methods(Brovey, IHS, PCA, HPF, CN, and MWD) with panchromatic and multispectral images of IKONOS and developed the registration method for applying to SPOT-5 satellite image and RADARSAT SAR satellite image. As the result of tests on image fusion and image registration, we could find that MWD and HPF methods showed the good result in term of visual comparison analysis and statistical analysis. And we could extract patches which depict detailed topographic information from SPOT-5 and RADARSAT and obtain encouraging results in image registration.

Ground Settlement Monitoring using SAR Satellite Images (SAR 위성 영상을 이용한 도심지 지반 침하 모니터링 연구)

  • Chungsik, Yoo
    • Journal of the Korean Geosynthetics Society
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    • v.21 no.4
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    • pp.55-67
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    • 2022
  • In this paper, fundamentals and recent development of the interferometric synthetic aperture radar, known as InSAR, technique for measuring ground deformation through satellite image analysis are presented together with case histories illustrating its applicability to urban ground deformation monitoring. A study area in Korea was selected and processed based on the muti-temporal time series InSAR analysis, namely SBAS (Small Baseline Subset)-InSAR and PS (Persistent Scatterers)-InSAR using Sentinel-1A SAR images acquired from the year 2014 onward available from European Space Agency Copernicus Program. The ground settlement of the study area for the temporal window of 2014-2022 was evaluated from the viewpoint of the applicability of the InSAR technique for urban infrastructure settlement monitoring. The results indicated that the InSAR technique can reasonably monitor long-term settlement of the study area in millimetric scale, and that the time series InSAR technique can effectively measure ground settlement that occurs over a long period of time as the SAR satellite provides images of the Korean Peninsula at regular time intervals while orbiting the earth. It is expected that the InSAR technique based on higher resolution SAR images with small temporal baseline can be a viable alternative to the traditional ground borne monitoring method for ground deformation monitoring in the 4th industrial era.

The Potential of Satellite SAR Imagery for Mapping of Flood Inundation

  • Lee, Kyu-Sung;Hong, Chang-Hee;Kim, Yoon-Hyoung
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.128-133
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    • 1998
  • To assess the flood damages and to provide necessary information for preventing future catastrophe, it is necessary to appraise the inundated area with more accurate and rapid manner. This study attempts to evaluate the potential of satellite synthetic aperture radar (SAR) data for mapping of flood inundated area in southern part of Korea. JERS L-band SAR data obtained during the summer of 1997 were used to delineate the inundated areas. In addition, Landsat TM data were also used for analyzing the land cover condition before the flooding. Once the two data sets were co-registered, each data was separately classified. The water surface areas extracted from the SAR data and the land cover map generated using the TM data were overlaid to determine the flood inundated areas. Although manual interpretation of water surfaces from the SAR image seems rather simple, the computer classification of water body requires clear understanding of radar backscattering behavior on the earth's surfaces. It was found that some surface features, such as rice fields, runaway, and tidal flat, have very similar radar backscatter to water surface. Even though satellite SAR data have a great advantage over optical remote sensor data for obtaining imagery on time and would provide valuable information to analyze flood, it should be cautious to separate the exact areas of flood inundation from the similar features.

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Application of Bimodal Histogram Method to Oil Spill Detection from a Satellite Synthetic Aperture Radar Image

  • Kim, Tae-Sung;Park, Kyung-Ae;Lee, Min-Sun;Park, Jae-Jin;Hong, Sungwook;Kim, Kum-Lan;Chang, Eunmi
    • Korean Journal of Remote Sensing
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    • v.29 no.6
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    • pp.645-655
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    • 2013
  • As one of segmentation techniques for Synthetic Aperture Radar (SAR) image with oil spill, we applied a bimodal histogram method to discriminate oil pixels from non-oil pixels. The threshold of each moving window was objectively determined using the two peaks in the histogram distribution of backscattering coefficients from ENVISAT ASAR image. To reduce the effect of wind speed on oil spill detection, we selected ASAR image which satisfied a limit of wind speeds for successful detection. Overall, a commonly used adaptive threshold method has been applied with a subjectively-determined single threshold. In contrast, the bimodal histogram method utilized herein produces a variety of thresholds objectively for each moving window by considering the characteristics of statistical distribution of backscattering coefficients. Comparison between the two methods revealed that the bimodal histogram method exhibited no significant difference in terms of performance when compared to the adaptive threshold method, except for around the edges of dark oil spots. Thus, we anticipate that the objective method based on the bimodality of oil slicks may also be applicable to the detection of oil spills from other SAR imagery.

Classification of Water Areas from Satellite Imagery Using Artificial Neural Networks

  • Sohn, Hong-Gyoo;Song, Yeong-Sun;Jung, Won-Jo
    • Korean Journal of Geomatics
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    • v.3 no.1
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    • pp.33-41
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    • 2003
  • Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

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Velocity Estimation of Moving Targets on the Sea Surface by Azimuth Differentials of Simulated-SAR Image

  • Yang, Chang-Su;Kim, Youn-Seop;Ouchi, Kazuo
    • Korean Journal of Remote Sensing
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    • v.26 no.3
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    • pp.297-304
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    • 2010
  • Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

Analysis of Water Surface Area Change in Reservoir Using Satellite Images (위성영상을 이용한 저수지 수체면적 변화 분석)

  • Kim, Joo-Hun;Kim, Dong-Phil
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.44 no.5
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    • pp.629-636
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    • 2024
  • The purpose of this study is to monitor changes in the water surface of reservoirs in verifiable areas in Korea using satellite images and to analyze the water surface area and water storage. The target area of this study is the Daecheong dam of the Geumgang(Riv.), which supplies water to some areas in the Chungcheong area. A study was conducted to detect water surface area by using the Sentinel-1(SAR-C) image and the optical image of Sentinel-2(MSI) among the various observation sensors of satellite images. The correlation between the reservoir's water storage volume, which is ground measurement data, and the extracted water surface area was analyzed. As a result of the analysis, the coefficient of determination(R2) between water surface area and daily storage using SAR images was analyzed to be 0.9242, and in the analysis using Sentinel-2's MSI optical image, it was analyzed to be correlated at 0.8995. In addition, it is analyzed that the water storage volume of the water surface area extracted from the image using the relationship between the water storage volume and the water surface area represents a hydrograph similar to the actual water storage volume. This study is a basic study for the use of satellite images in unmeasured/non-access areas such as North Korea, and plans to conduct a study to analyze annual changes and long-term trends in major dam reservoirs in North Korea by reflecting the results obtained through this study.

Analysis of SAR Interference Suppression Techniques using Eigen-subspace based Filter (고유치 기반 필터를 이용한 위성 SAR 영상 간섭신호 제거 기법)

  • Lee, Bo-Yun;Kim, Bum-Seung;Song, Jung-Hwan;Lee, Woo-Kyung
    • Journal of Satellite, Information and Communications
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    • v.12 no.3
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    • pp.63-68
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    • 2017
  • SAR(Synthetic Aperture Radar) uses electromagnetic signals to acquire ground information and has been used for wide coverage reconnaissance missions regardless of weather conditions. However SAR is known to be vulnerable to interference signals by other communication devices or radar instruments and may suffer from undesirable performance degradations and image quality. In this paper, a modified Eigen-subspace based filter is proposed that can be easily applied to SAR images affected by interference signals. The method of constructing Eigen-subspace based filter is briefly described and various simulations are performed to show the performance of the interference mitigation process. The suppression filter is applied to a ALOS PALSAR raw data affected by interfering signals in order to verify its superiority over the Notch filter.

An efficient ship detection method for KOMPSAT-5 synthetic aperture radar imagery based on adaptive filtering approach

  • Hwang, JeongIn;Kim, Daeseong;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.33 no.1
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    • pp.89-95
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    • 2017
  • Ship detection in synthetic aperture radar(SAR)imagery has long been an active research topic and has many applications. In this paper,we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum ship sizes and detects ships from the reference image, to which a Non-Local means (NL-means) filter is applied for speckle de-noising and a differential image created from the difference between the reference image and the median filtered image. As the pixels of the ship in the SAR imagery have sufficiently higher values than the surrounding sea, the ship detection process is composed primarily of filtering based on this characteristic. The performance test for this method is validated using KOMPSAT-5 (Korea Multi-Purpose Satellite-5) SAR imagery. According to the accuracy assessment, the overall accuracy of the region that does not include land is 76.79%, and user accuracy is 71.31%. It is demonstrated that the proposed detection method is suitable to detect ships in SAR imagery and enables us to detect ships more easily and efficiently.

SATELLITE SAR OBSERVATION OF SOLITARY INTERNAL WAVE OCCURRENCE IN THE NORTHERN SOUTH CHINA SEA

  • Zheng, Quanan;Susanto, R. Dwi;Ho, Chung-Ru;Song, Y. Tony;Xu, Qing
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.938-941
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    • 2006
  • Satellite synthetic aperture radar (SAR) images from 1995 to 2001 and field measurements of sea surface wind, sea state, and vertical stratification are used for statistical analyses of internal wave (IW) occurrence and SAR imaging conditions in the northern South China Sea (NSCS). Latitudinal distribution of IW packets shows that 22% of IW packets distributed in the east of $118^{\circ}E$ and 78% of IW packets in the west of $118^{\circ}E$. The yearly distribution of IW occurrence frequencies reveals an interannual variability. The monthly SAR-observed IW occurrence frequencies show that the high frequencies are distributed from April to July and reach a peak in June. The low occurrence frequencies are distributed in winter from December to February of next year. These statistical features are explained by solitary wave dynamics.

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