• Bulletin of the Korean Space Science Society
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• 2000.10a
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• pp.110-110
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• 2000

No Abstract, See Full Text

• Atmosphere
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• v.17 no.1
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• pp.101-108
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• 2007

To observe and analyze the cloud and fog characteristics, the METeorological Research Institute (METRI) has established the Cloud Physics Observation System (CPOS) by implementing the cloud observation instruments: Forward Scattering Spectrometer Probe (FSSP), PARticle SIze and VELocity (PARSIVEL), Microwave Radiometer (MWR), Micro Rain Radar (MRR), and 3D-AWS at the Daegwallyeong Enhanced Mountain Weather Observation Center. The cloud-related products of CPOS and the validation status for the size distribution of FSSP, the precipitable water of MWR, and the rainfall rate of MRR and PARSIVEL are described.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.351-361
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• 2003

As the launches of a series of remote sensing satellites, there are various multiresolution and multi-spectral images available nowadays. This diversity in remotely sensed image data has created a need to be able to integrate data from different sources. The C-band imaging radar of ERS-2 due to its high sensitivity to coastal wetlands holds tremendous potential in mapping and monitoring coastal wetland features. This paper investigates the advantages of using ERS-2 SAR data combined with IRS-ID LISS-3 data for mapping complex coastal wetland features of Tamil Nadu, southern India. We present a methodology in this paper that highlights the mapping potential of different combinations of filtering and integration techniques. The methodology adopted here consists of three major steps as following: (i) speckle noise reduction by comparative performance of different filtering algorithms, (ii) geometric rectification and coregistration, and (iii) application of different integration techniques. The results obtained from the analysis of optical and microwave image data have proved their potential use in improving interpretability of different coastal wetland features of southern India. Based visual and statistical analyzes, this study suggests that brovey transform will perform well in terms of preserving spatial and spectral content of the original image data. It was also realized that speckle filtering is very important before fusing optical and microwave data for mapping coastal mangrove wetland ecosystem.

• Proceedings of the KSRS Conference
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• v.2
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• pp.1015-1018
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• 2006

The use of passive microwave data for estimating sea-ice thickness is limited by strong dependence of emissivity on near-surface brine. However, this particular characteristic becomes a basis for an algorithm to estimate thickness of thin sea-ice if a thickness-salinity-emissivity relationship is established. This study aims at developing an algorithm to estimate sea ice thickness on the basis of this relationship. In order to establish a thickness-salinity-emissivity relationship, we have conducted multi-platform synchronous observations in the Sea of Okhotsk. We note a positive relationship between thickness and brightness temperature. From observations, we also establish an empirical relationship between salinity and emissivity, thus between thickness and brightness temperature. The derived relationship is qualitatively similar to the one based on Hoekstra and Cappillino's formulation. Our results suggest that for thin sea-ice in the winter period there is potential to develop an algorithm to estimate sea-ice thickness.

• Korean Journal of Remote Sensing
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• v.11 no.2
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• pp.29-42
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• 1995

A typhoon center location and its intensity from the 54.96GMz channel of Microwave Sounding Unit(MSU) on board the NOAA satellite is analyzed. NOAA satellite MSU channel 3 data may delineate the development and dissipation of the upper tropospheric warm core associated with a typhoon. The typhoon warm core is related to microwave imagery of 250hPa temperature field (54.96GMz). The typhoon center intensity, surface center pressure and maximum wind speed at the eye well, correlate to horozontal Laplacian of an upper tropospheric temperature field. The typhoon center is found from the analysis of 250hPa temperature field. The excellent correlation is found between the horizontal Laplacian of an tropospheric temperature field and surface maximum wind speed, another correlation is found between the warm temperature anomaly and surface pressure anomaly.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.173-180
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• 2014

The development process of a L-Band microwave radiometer for remote sensing of soil-moisture are described in this paper. Achieving the development aim of the measurement accuracy within 2% for soil moisture content of 0~50%, the requirements and specifications of the microwave radiometer and its receiver are drawn. The receiver with high gain, high sensitivity is designed and implemented to satisfy these requirements and specifications. The receiver has the bandwidth of 40 MHz, the system gain of 50 dB and the sensitivity of average value 0.19 K, maximum value 0.313K at 1390 MHz.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.131-140
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• 2011

In this study, temporal variations of the Advanced Microwave Scanning Radiometer E (AMSR-E) soil moisture products were evaluated using ground based measurements from the Haenam flux monitoring network site for two years (2004 and 2006). Even if there were major comparison issues including spatial resolutions, AMSR-E soil moisture production showed a great potential to replicate temporal variability patterns with ground based measurements. Additional intensive validation efforts should be conducted at a variety of field conditions including vegetation type for better utilization of remotely sensed soil moisture and understanding of the land surface-atmosphere interactions in the view of hydrometeorology.

• Proceedings of the KSRS Conference
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• v.1
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• pp.386-389
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• 2006

The sea surface wind speed (SSWS) derived by microwave radiometer can be contaminated by change of microwave brightness temperature owing to the angle between the sensor azimuth and the wind direction (Relative Wind Direction). We attempt to correct the contamination to the SSWS derived by Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing Satellite II (ADEOS-II), by applying the method proposed by Konda and Shibata (2004). The improvement of accuracy of the SSWS estimation amounts to roughly 60% of the error caused by the RWD effect.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.324-327
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• 2008

Microwave remote sensing has great potential, especially in monsoon Asia, since optical observations are often hampered by cloudy conditions. The radar backscattering characteristics of rice crop were investigated with a ground-based automatic scatterometer system. The system was installed inside a shelter in an experimental paddy field at the National Institute of Agricultural Science and Technology (NIAST) before transplanting. The rice cultivar was a kind of Japonica type, called Chuchung. The scatterometer system consists of X-band antennas, HP8720D vector network analyzer, RF cables, and a personal computer that controls frequency, polarization and data storage. This system automatically measures fully-polarimatric backscattering coefficients of rice crop every 10 minutes, accompanied by a digital camera that takes pictures in a fixed position with the same interval. The backscattering coefficients were calculated by applying a radar equation. Plant variables, such as leaf area index (LAI), biomass, plant height and weather conditions were measured periodically throughout the rice growth season. We have performed polarimetric decomposition of paddy data such as single, double and volume scattering to extract the scattering information effectively. We investigated the relationships between backscattering coefficients and the plant variables.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.277-288
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• 2011

Cloudsat satellite data is sensitive to snowfall and collected during each month beginning with Dec 2007 and ending Feb 2008. In this study, we attempt to develop a snowfall retrieval algorithm using a combination of radiometer and cloud radar data. We trained data from the relation between brightness temperature measurements from NOAA's Advanced Microwave Sounder Unit-B(AMSU-B) and the radar reflectivity of the 2B-GEOPROF product from W-band(94 GHz) cloud radar onboard Cloudsat and applied it to the Korea peninsula. We use a principal components analysis to quantify the variations that are the result of the radiometric signatures of snowfall from those of the surface. Finally, we quantify the correlation between the higher principal component (orthogonal to surface variability) of the microwave radiances and the precipitation-sensitive CloudSat radar reflectivities. This work summarizes the results of applying this approach to observations over the East Sea during Feb. 2008. The retrieved data show reasonable estimation for snowfall rate compared with Cloudsat vertical image.