• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.109-114
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• 2010

This paper studies the origin of low back-scattering area appeared on the SAR image taken on the coastal waters off the southeast coast of Korea on July 5, 2000. Cold waters were frequently observed during summer on this coastal waters, and quasi-simultaneously taken AVHRR and SeaWiFS images also showed cold surface waters and high concentration of chlorophyll-a, respectively. By synergetic analysis of multi-sensor satellite images, it is strongly suggested that the cold and nutrient rich upwelling waters caused the high phytoplankton density and high biological activities in the water producing natural films for low back-scattering.

• 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.

• 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.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.389-392
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• 2000

In this paper, we propose a novel post processing method of deconvolution for SAR images based on phase extension inverse filtering, which improves spatial resolution as well as effectively eliminates sidelobes with low computational complexity. It extends the bandwidth only to control the magnitude of the processed SAR data without distortions of the phase in frequency domain unlike the other techniques such as spatially variant apodization (SVA), and other deconvolution techniques. We compare the image processed by the proposed method with images processed by uniform weighting function, Hamming weighting function whose coefficient is 0.75, and SVA.

• Proceedings of the KSRS Conference
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• v.2
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• pp.888-891
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• 2006

SAR image is not dependent on the weather condition and Sun's electromagnetic energy. But geometric distortions exist in almost all radar image, it need to be correction. The Radarsat-1 SAR images are used to monitoring of moisture acquired in May 1/1998 and May 25/1998. Radarsat-1 C band data is sensitive on moisture condition. Study area is located in Non-san site. It is made up almost agricultural area and a little of forest area. In May, Rice-planting is started in the midland of Korea. So moisture condition is undergoing many changes. Forest area need to be terrain effect removal for accurately results because it is included in layover, shadow, and so on. Results of land-cover moisture condition map are useful tool for fields of agriculture, forestry industry, and disaster.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.407-407
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• 2002

The most widespread techniques for DEM generation are stereoscopy for optical sensor images and interfereometry for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. In this paper, different strategies for fusing SAR and optical data are combined to derive high quality DEM products. The filtering techniques, which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. By taking advantage of the fact that errors of the DEMs are of different nature using the filtering technique, affected part are filtered and replaced by those of the counterpart and is tested with two sets of SPOT and ERS DEM, resulting in a remarkable improvement in DEM. for the analysis of results, the reference DEM is generated from digital base map(1:5000).

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.433-437
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• 2006

SAR image is not dependent on the weather condition and Sun's electromagnetic energy. But geometric distortions exist in almost all radar image, it need to be correction. The Radarsat-1 SAR images are used to monitoring of moisture acquired in May 1/1998 and May 25/1998. Radarsat-1 C band data is sensitive on moisture condition. Study area is located in Non-san site. It is made up almost agricultural area and a little of forest area. In May, Rice-planting is started in the midland of Korea. So moisture condition is undergoing many changes. Forest area need to be terrain effect removal for accurately results because it is included in layover, shadow, and so on. Results of land-cover moisture condition map are useful tool for fields of agriculture, forestry industry, and disaster.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.360-362
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• 2003

This paper presents simple feature-based approaches for full- and/or semi-automatic extraction, selection, and localization (center-determination) of ground control points (GCPs) for radargrammetry using airborne synthetic aperture radar (SAR) images. Test results using airborne NASA/JPL TOPSAR images in Taiwan verify that the registration accuracy is about 0.8${\sim}$1.4 pixels. In c.a. 30 minutes, 1500${\sim}$3000 GCPs are extracted and their point centers in a SAR image of about 512 ${\times}$ 512 pixels are determined on a personal computer.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.431-439
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• 2010

Cross-interferometic synthetic aperture radar (CInSAR) technique from ERS-2 and Envisat images is capable of generating submeter-accuracy digital elevation model (DEM). However, it is very difficult to produce high-quality CInSAR-derived DEM due to the difference in the azimuth and range pixel size between ERS-2 and Envisat images as well as the small height ambiguity of CInSAR interferogram. In this study, we have proposed an efficient method to overcome the problems, produced a high-quality DEM over northern Alaska, and compared the CInSAR-derived DEM with the national elevation dataset (NED) DEM from U.S. Geological Survey. In the proposed method, azimuth common band filtering is applied in the radar raw data processing to mitigate the mis-registation due to the difference in the azimuth and range pixel size, and differential SAR interferogram (DInSAR) is used for reducing the unwrapping error occurred by the high fringe rate of CInSAR interferogram. Using the CInSAR DEM, we have identified and corrected man-made artifacts in the NED DEM. The wave number analysis further confirms that the CInSAR DEM has valid Signal in the high frequency of more than 0.08 radians/m (about 40m) while the NED DEM does not. Our results indicate that the CInSAR DEM is superior to the NED DEM in terms of both height precision and ground resolution.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.522-525
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• 2004

Interferometry SAR (InSAR) is a technique to generate topographic map from complex data pairs observed by antennas at different locations. However, to obtain topographic information using InSAR is difficult task because it requires series of complicated process including phase unwrapping and precise recovery of the SAR geometry. Especially, accuracy of the DEM (Digital Elevation Model) produced by repeat pass single SAR pair could be influenced by atmospheric effect. Recently, a new InSAR technique to improve accuracy of DEM has been introduced that utilizes low resolution DEM with a number of SAR image pairs. The coarse DEM plays an important role in reducing phase unwrapping error caused by layover and satellite orbit error. In this study, we implemented DInSAR (Differential InSAR) method which combines low resolution DEMs and ERS tandem pair images. GTOPO30 DEM with 1km resolution, SRTM-3 DEM with 100m resolution, and DEM with 10m resolution derived from 1:25,000 digital vector map were used to investigate feasibility of DInSAR. The accuracy of the DEMs generated both by InSAR and DInSAR was evaluated.