• Bulletin of the Korean Space Science Society
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• 1999.09a
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• pp.43-43
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• 1999

No Abstract, See Full Text

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.538-541
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• 2005

Tidal flats develop along the south coast ofthe Korean peninsula. These areas are famous for sea farming. Specially, strong and coherent radar backscattering signals are observed over oyster sea farms that consist of artificial structures. Tide height in oyster farm is possible to measure by using interferometric phase and intensity of SAR data. It is assumed that the radar signals from oyster farm could be considered as double-bouncing returns by vertical and horizontal bars. But, detailed backscattering mechanism and polarimetric characteristics in oyster farm had not been well studied. We could not demonstrate whether the assumption is correct or not and exactly understand what the properties of back scattering were in oyster farm without full polarimetric data. The results of AIRSAR L-band POLSAR data, experiments in laboratory and JERS-l images are discussed. We carried out an experiment simulating a target structure using vector network analyser (Y.N.A.) in an anechoic chamber at Niigata University. Radar returns from vertical poles are stronger than those from horizontal poles by 10.5 dB. Single bounce components were as strong as double bounce components and more sensitive to antenna look direction. Double bounce components show quasi-linear relation with height of vertical poles. As black absorber replaced AI-plate in bottom surface, double bounce in vertical pole decreased. It is observed that not all oyster farms are characterized by double bounced scattering in AIRSAR data. The image intensity of the double bounce dominant oyster farm was investigated with respect to that of oyster farm dominated by single bounce in JERS-l SAR data. The image intensity model results in a correlation coefficient (R2 ) of 0.78 in double bounce dominant area while that of 0.54 in single bouncing dominant area. This shows that double bounce dominant area should be selected for water height measurement using In8AR technique.

• Proceedings of the KSRS Conference
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• v.1
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• pp.7-10
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• 2006

Four programs, i.e. TRMM, ADEOS2, ASTER, and ALOS are going on in Japanese Earth Observation programs. TRMM and ASTER are operating well, and TRMM operation will be continued to 2009. ADEOS2 was failed, but AMSR-E on Aqua is operating. ALOS (Advanced Land Observing Satellite) was successfully launched on $24^{th}$ Jan. 2006. ALOS carries three instruments, i.e., PRISM (Panchromatic Remote Sensing Instrument for Stereo Mapping), AVNIR-2 (Advanced Visible and Near Infrared Radiometer), and PALSAR (Phased Array L band Synthetic Aperture Radar). PRISM is a 3 line panchromatic push broom scanner with 2.5m IFOV. AVNIR-2 is a 4 channel multi spectral scanner with 10m IFOV. PALSAR is a full polarimetric active phased array SAR. PALSAR has many observation modes including full polarimetric mode and scan SAR mode. After the unfortunate accident of ADEOS2, JAXA still have plans of Earth observation programs. Next generation satellites will be launched in 2008-2012 timeframe. They are GOSAT (Greenhouse Gas Observation Satellite), GCOM-W and GCOM-C (ADEOS-2 follow on), and GPM (Global Precipitation Mission) core satellite. GOSAT will carry 2 instruments, i.e. a green house gas sensor and a cloud/aerosol imager. The main sensor is a Fourier transform spectrometer (FTS) and covers 0.76 to 15 ${\mu}m$ region with 0.2 to 0.5 $cm^{-1}$ resolution. GPM is a joint project with NASA and will carry two instruments. JAXA will develop DPR (Dual frequency Precipitation Radar) which is a follow on of PR on TRMM. Another project is EarthCare. It is a joint project with ESA and JAXA is going to provide CPR (Cloud Profiling Radar). Discussions on future Earth Observation programs have been started including discussions on ALOS F/O.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.3
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• pp.273-288
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• 1997

In this work, the electromagnetic waves scattered from 2-dimensional random rough surfaces are characterized by the $4\times4$ Mueller matrix elements. The full wave solutions are used to compute these elements. The results of the full wave solutions for 1-dimensional random rough surfaces were shown to agree well with those of the experiment and the method of moments. The Mueller matrix elements are related to the like and cross polarized radar cross sections as well as to the relative phase of the vertically and horizontally polarized waves. The $4\times4$ Mueller matrix elements completely characterize electromagnetic scattering from target. The computed results of this paper can be useful to the field of active remote sensing or RCS.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.878-886
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• 2011

The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.463-470
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• 2016

In this paper, we introduce a method of scattering centers extraction using the polarimetric data. VIRAF software based on the PO (Physical Optics) and PTD(Physical Theory of Diffraction) were used to calculate the surface scattering and the edge or wedge scattering, respectively. In addition, by using the unitary transformation, 4-channel data based on the linear polarization basis were converted to 2-channel data based on the left/vertical-circular polarization basis, leading to data compression coherently. The scattering mechanism was analyzed in terms of the polarization states and different look angles by using the scattering center of a target extracted by the 2D RELAX algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.191-201
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• 2011

Soybean has widely grown for its edible bean which has numerous uses. Microwave remote sensing has a great potential over the conventional remote sensing with the visible and infrared spectra due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the crop conditions of a soybean field. Polarimetric backscatter data at L, C, and X-bands were acquired every 10 minutes on the microwave observations at various soybean stages. The polarimetric scatterometer consists of a vector network analyzer, a microwave switch, radio frequency cables, power unit and a personal computer. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. The backscattering coefficients were calculated from the measured data at incidence angle $40^{\circ}$ and full polarization (HH, VV, HV, VH) by applying the radar equation. The soybean growth data such as leaf area index (LAI), plant height, fresh and dry weight, vegetation water content and pod weight were measured periodically throughout the growth season. We measured the temporal variations of backscattering coefficients of the soybean crop at L, C, and X-bands during a soybean growth period. In the three bands, VV-polarized backscattering coefficients were higher than HH-polarized backscattering coefficients until mid-June, and thereafter HH-polarized backscattering coefficients were higher than VV-, HV-polarized back scattering coefficients. However, the cross-over stage (HH > VV) was different for each frequency: DOY 200 for L-band and DOY 210 for both C and X-bands. The temporal trend of the backscattering coefficients for all bands agreed with the soybean growth data such as LAI, dry weight and plant height; i.e., increased until about DOY 271 and decreased afterward. We plotted the relationship between the backscattering coefficients with three bands and soybean growth parameters. The growth parameters were highly correlated with HH-polarization at L-band (over r=0.92).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1002-1004
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• 2003

A ground-based, C-band full polarimetric mobile Scatterometer system has been developed in Malaysia with collaboration between Malaysian Centre for Remote Sensing (MACRES) and Multimedia University (MMU). The main purpose of this system is to measure and monitor backscattering coefficient, ${\sigma }^0$, for earth terrain such as paddy fields, forest and soil surfaces. This paper describes the preliminary results on radar backscatter measurement from paddy field using the mobile C-band Scatterometer system. The measurement campaign was conducted at Sungai Burung area in April 2003. Real time data were collected using four polarization modes (HH, HV, VV and VH), at various incidence angles ranging from 0$^0$ to 60$^0$. The measurement data show consistent results as compared to other reports, which verify the capability of this Scatterometer system as a useful tool for remote sensing.

• Proceedings of the KSRS Conference
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• v.1
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• pp.390-393
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• 2006

It is well known that synthetic aperture radar (SAR) provides information on ocean winds and surface waves. SAR data are of particularly high value in extreme weather conditions, as radar is able to penetrate the clouds providing information on different ocean surface processes. In this presentation some recent results on SAR observation of extreme wind and ocean wave conditions is summarised. Particular emphasize is put on the investigation of typhoons and extratropical cyclones in the North Pacific. The study is based on the use of ENVISAT ASAR wide swath images. Wide swath and scansar data are well suited for a detailed investigation of cyclones. Several examples like, e.g., typhoon Talim will be presented, demonstrating that these data provide valuable information on the two dimensional structure of the both the wind and the ocean wave field. Comparisons of the SAR observation with parametric and numerical model data will be discussed. Some limitations of standard imaging models like, e.g., CMOD5 for the use in extreme wind conditions are explained and modifications are proposed. Finally the study summarizes the capabilities of new high resolution TerraSAR-X mission to be launched in October 2006 with respect to the monitoring of extreme weather conditions. The mission will provide a spatialresolution up to 1m and has full polarimetric capabilities.