• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.485-490
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• 1999

Wind vector information over the ocean is currently obtained using multiple beam scatterometer data. The scatterometers on ERS-1/2 generate wind vector information with a spatial resolution of 50km and accuracies of $\pm$2m/s in wind speed and $\pm$20$^{\circ}$ in wind direction. Synthetic aperture radar (SAR) data over the ocean have the potential of providing wind vector information independent of weather conditions with finer resolution. Finer resolution wind vector information can often be useful particularly in coastal regions where the scatterometer wind information is often corrupted because of the lower resolution system characteristics which is often contaminated by the signal returns from the coastal areas or ice in the case of arctic environments. In this paper we tested CMOD_4 and CMOD_IFR2 algorithms for extracting the wind vector from SAR data. These algorithms require precise estimation of normalized radar cross-section and wind direction from the SAR data and the local incidence angle. The CMOD series algorithms were developed for the C-band, VV-Polarized SAR data, typically for the ERS SAR data. Since RADARSAT operates at the same C-band but with HH-Polarization, the CMOD series algorithms should not be used directly. As a preliminary approach of resolving with this problem, we applied the polarization ratio between the HH and VV polarizations in the wind vectors estimation. Two test areas, one in front of Inchon and several sites around Jeju island were selected and investigated for wind vector estimation. The new results were compared with the wind vectors obtained from CMOD algorithms. The wind vector results agree well with the observed wind speed data. However the estimation of wind direction agree with the observed wind direction only when the wind speed is greater than approximately 3.0m/s.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.147-152
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• 2005

This paper proposes an evaluates a new approach to detect ships as targets from Radarsat-1 SAR (Synthetic Aperture Radar) imagery in the vicinity of Korean peninsula. To be more specific, a labeling technique and morphological filtering in conjunction with some other methods are employed to automatically detect the ships. From the test, the ships are revealed to be detected. For ground truth data, information from a radar system is used, which allows assessing accuracy of the approach. The results showed that the proposed approach has the high potential in automatically detecting the ships.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.7-9
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• 2003

The objective of this study is to evaluate flood risk area by integrating GIS and RADARSAT data. The study area, Northeast Thailand, is subject to flood during the rainy season. The main data used in this evaluation included RADARSAT data, landform and topographic map. The evaluation was conducted by overlay operation of flood area in 2001, land form and buffer region beyond the flood areas with the selection criteria defined. Most of the flood risk areas were found in the low lying land form within the buffer region. The cloud penetrating capabilities of SAR is only a source of information for effectively assessment of flood risk area in Northeast Thailand.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.57-59
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• 2004

This paper reports the observation of the interferometric synthetic aperture radar (InSAR) phase anomaly on a newly reclaimed mudflat, Hwaong, in west coast of Korea, detected by a series of Radarsat-l SAR data obtained mostly during 2003. The observed phase anomaly could be from subsidence of mud land caused by volumetric contraction of mud in dry season. This process must have been initiated from March 2002 when tidal water supply to this region was permanently blocked by the newly constructed embankment. The maximum subsidence rate measured from InSAR signal is about 3 cm per month. The local heterogeneity of the subsidence rate over the reclaimed mudflat may indicate various mud composition, surface-subsurface hydrological processes, or subsurface information of the mud and basement rock structure. In-situ measurement must follow to support this observation from space.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.85-90
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• 2000

백두산 지역의 JERS-1 SLC 영상과 볼리비아 지역의 RADARSAT 영상에 대해 각각 interferometry와 radargrammetry를 이용하여 수치표고모형을 제작하였다. Interferometry 는 coregistration, interferogram 작성, phase unwrapping 과정으로 나눠지는데 temporal decorrelation으로 낮은 coherence, 부정확한 궤도정보가 DEM의 정확도를 저하시키는 주요 원인으로 작용하였다. Radargrammetry는 photogrammetry와 동일한 처리과정, 즉 GCP를 이용한 stereo model 설정, 영상 matching, 고도추출단계로 이루어지지만 광학영상 과는 다른 SAR 영상의 기하학적, 방사적 특성이 고려되어야 한다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.37-37
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• 2003

Rice is one of the most important crop in the world and is a major export of Thailand. Optical sensors are not useful for rice monitoring, because most cultivated areas are often obscured by cloud during the growing period, especially in South East Asia. Spaceborne Synthetic Aperture Radar (SAR) such as RADARSAT, can see through regardless of weather condition which make it possible to monitor rice growth and to retrieve rice acreage, using the unique temporal signature of rice fields. This paper presents the result of a study of examining the backscatter behavior of rice using multi-temporal RADARSAT dataset. Ground measurements of paddy parameters and water and soil condition were collected. The ground truth information was also used to identify mature rice crops, orchard, road, residence, and aquaculture ponds. Land use class distributions from the RADARSAT image were analyzed. Comparison of the mean DB of each land use class indicated significant differences. Schematic representation of temporal backscatter of rice crop were plotted. Based on the study carried out in Pathum Thani Province test site, the results showed variation of sigma naught from first tillering vegatative phase until ripenning phase. It is suggested that at least, three radar data acquisitions taken at 3 stages of rice growth circle namely; those are at the beginning of rice growth when the field is still covered with water, in the ear differentiation period, and at the beginning of the harvest season, are required for rice monitoring. This pilot project was an experimental one aiming at future operational rice monitoring and potential yield predicttion.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.569-579
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• 2013

In this study, land-cover classification was implemented using features extracted from multi-temporal SAR data through 3D wavelet transform and the applicability of the 3D wavelet transform as a feature extraction approach was evaluated. The feature extraction stage based on 3D wavelet transform was first carried out before the classification and the extracted features were used as input for land-cover classification. For a comparison purpose, original image data without the feature extraction stage and Principal Component Analysis (PCA) based features were also classified. Multi-temporal Radarsat-1 data acquired at Dangjin, Korea was used for this experiment and five land-cover classes including paddy fields, dry fields, forest, water, and built up areas were considered for classification. According to the discrimination capability analysis, the characteristics of dry field and forest were similar, so it was very difficult to distinguish these two classes. When using wavelet-based features, classification accuracy was generally improved except built-up class. Especially the improvement of accuracy for dry field and forest classes was achieved. This improvement may be attributed to the wavelet transform procedure decomposing multi-temporal data not only temporally but also spatially. This experiment result shows that 3D wavelet transform would be an effective tool for feature extraction from multi-temporal data although this procedure should be tested to other sensors or other areas through extensive experiments.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.234-237
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• 2007

이 연구에서는 C 밴드와 L 밴드 다편광 NASA JPL AirSAR 자료를 농작물 구분에 사용함에 있어서 자료 융합의 효과를 살펴보고자 하였다. Target decomposition으로부터 얻어지는 산란특성과 관련된 특징들을 입력으로 support vector machines을 개별 파장대 편광 SAR 자료의 분류에 이용하였으며 C 밴드와 L 밴드 자료의 사후확률을 ${\tau}$모델을 이용하여 융합하였다. 적용 결과 L 밴드 자료가 C 밴드 자료에 비해 농작물 구분에 적절한 투과 심도를 나타내어 상대적으로 높은 분류 정확도를 나타내었지만，자료 융합을 통해 보다 향상된 분류 정확도를 얻을 수 있었다. 이 연구에서 제시된 방법론은 앞으로 이용이 가능할 C 밴드 Radarsat-2 자료와 L 밴드 ALOS 자료에 적용이 가능할 것으로 판단된다.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.205-208
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• 2006

Based on SAR signatures for bars, bar transformation is investigated from 2000 to 2005, and monitoring of suspended-silt transportations from terrestrial runoff is tried to understand the morphology during the events of severe rain storm. SAR data did not reveal clearly the bar locations because of most of data acquisitions during high tides form 6.8 m to 9.0 m. Even though the problem, it could be said that in the estuary vegetated area and natural levees are developed well, but bars are shifted after an event like a flood. It is also showed that suspended solids such as silt transported through the estuary could contributed highly to a sedimentation environment around Incheon. A navigational route could be designed with a minimum width of about 200m.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.243-245
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• 2007

This study was begun to classify the paddy fields by the rice varieties and to monitor the temporal change in rice growth using SAR backscatter coefficients $({\sigma}^{circ})$. For nine fine-beam mode images of Radarsat-1 SAR, a growing period time-series of backscatter coefficients was set up from April to October in 2005, and was compared with the field-measured rice growth parameters such as LAI (leaf area index), plant height, fresh and dry biomass, and water content in grain and plant for 45 parcels in Dangjin-gun, Chungcheongnam Province, South Korea. The average backscatter coefficients for early-maturing rice varieties (13 parcels) were ranged from -18.17dB to -6.06dB and were lower than for medium-late maturing rice varieties during most of the growing season. At around the heading stage (July 30) for early-maturing rice, both rice crops showed the highest backscatter coefficient values and the difference was the greatest before harvesting early-maturing rice. The temporal difference in backscatter coefficients between rice varieties was expected to play a key role to identify early-maturing rice fields. On the other hand, comparison with field-measured rice growth parameters showed that the backscatter coefficients decreased or stayed on the plateau after heading stage even though the growth of rice canopy advanced.