• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1359-1361
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• 2003

A set of microwave remote sensing data collected with the newly developed UMass Imaging Wind and Rain Airborne Profiler (IWRAP) during the 2002 Atlantic Hurricane Season was analyzed to further our understanding of the effect of precipitation on scatterometer wind vector retrieval. Coincident surface wind speed and precipitation measurements were provided by the UMass Simultaneous Frequency Microwave Radiometer (SFMR). The differences between the wind estimations from IWRAP and SFMR under precipitation conditions of 0-100mm/hr and wind speed of 0-60m/s was calculated, from which the effect of precipitation on the wind vector retrieval using scatterometry is analyzed qualitatively.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.761-771
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• 2011

The sensitivity of microwave scattering to the dielectric properties and the geometric structure of soil surfaces makes radar remote sensing a challenge for a wide range of environmental issues directly related to the condition of natural surfaces. Especially, the potential for retrieving soil moisture with a high spatial and/or temporal resolution represents a significant contribution to hydrological and ecological modeling. This paper aims to review the current state of the art in SAR technology and methodological issues towards the discovery of a new potential accurate monitoring of soil moisture changes. In this paper, important parameters or constraints significantly affect the sensitivity of the measurements to soil moisture, such as roughness statistics, spatial resolution, and local topography, are discussed to improve the applicability of SAR remote sensing techniques. This study particularly intends to discuss important notes for developing smart and reliable methods capable of retrieving geophysical information.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.65-69
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• 2007

A L-Band microwave radiometer for remote sensing of sea and river surface salinity has been developed. The processes of the design and implementation of the microwave radiometer, and the experiment results are presented in this paper. The developed L-Band microwave radiometer was field-tested in Sum-Jin River. The initial results shows that the microwave radiometer measures the sea and river surface salinity with the sensitivity of 1.5psu successfully.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1349-1351
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• 2003

In this paper, theoretical channels model of Synthetic Aperture Radiometer is presented. Based on this model, how amplitude imbalance, phase imbalance and mutual coupling between the different channels effect brightness temperature image retrieving is analyzed. The computer simulation results are also presented to find out the cause of the along-track streaks usually appeared in the retrieved brightness temperature image. In addition, a new system calibration approach is introduced to solve this problem.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.9
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• pp.900-907
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• 2013

The development processes of a L-band microwave radiometer for remote sensing of water surface salinity are described in this paper. Achieving the development aim of the measurement accuracy within 2 psu for water surface salinity of 0~40 psu, 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 45 MHz, the system gain of 47 dB and the sensitivity of 0.41 K at 1,390 MHz. The effectiveness of the developed L-band microwave radiometer for remote sensing of water surface salinity is demonstrated experimentally. The results show the microwave radiometer can detect water surface salinity for 10~28 psu within the accuracy of 1.4 psu.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.491-495
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• 1999

We compared the satellite observed temperature with the radiosonde observed temperature in the Korean Peninsula. The radiosonde observed data were obtained from four upper air observation stations in the Korean Peninsula from 1981 to 1998, and that was compared with the satellite observed data of the channel-2 and channel-4 of microwave sounding unit(MSU) on board NOAA series of polar-orbiting satellites. The radiosonde data were reconstructed into monthly radiosonde T$_{b}$ using MSU weighting function. The monthly climatology shows radiosonde T$_{b2}$ is higher than MSU T$_{b2}$ in summer. The correlation between MSU T$_{b2}$ and radiosonde T$_{b2}$ is 0.72-0.76 and 0.73-0.81 between MSU T$_{b4}$ and radiosonde T$_{b4}$.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.26-28
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• 2008

Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.426-428
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• 2003

Optical and microwave remote sensing data have been widely used in land cover and land use classification. Thanks to the spectral absorption characteristics of ground object in visible and near infrared region, optical data enables to extract different land cover types according to their material composition like water body, vegetation cover or bare land. On the other hand, microwave sensor receives backscatter radiance which contains information on surface roughness, object density and their 3-D structure that are very important complementary information to interpret land use and land cover. Separate use of these data have brought many successful results in practice. However, the accuracy of the land use / land cover established by this methodology still has some problems. One of the way to improve accuracy of the land use / land cover classification is just combination of both optical and microwave data in analysis. In this paper for the research, the author used LANDSAT TM scene 127/45 acquired on October 21, 1992, JERS-1 SAR scene 119/265 acquired on October 27, 1992 and aerial photographs taken on October 21, 1992. The study area has been selected in Hanoi City and surrounding area, Vietnam. This is a flat agricultural area with various land use types as water rice, secondary crops like maize, cassava, vegetables cultivation as cucumber, tomato etc. mixed with human settlement and some manufacture facilities as brick and ceramic factories. The use of only optical or microwave data could result in misclassification among some land use features as settlement and vegetables cultivation using frame stages. By combination of multitemporal JERS-1 SAR and TM data these errors have been eliminated so that accuracy of the final land use / land cover map has been improved. The paper describes a methodology for data combination and presents results achieved by the proposed approach.

• Proceedings of the KSRS Conference
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• v.1
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• pp.150-152
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• 2006

The DISCOVER Project (${\underline{D}}istributed$ ${\underline{I}}nformation$ ${\underline{S}}ervices$ for ${\underline{C}}limate$ and ${\underline{O}}cean$ products and ${\underline{V}}isualizations$ for ${\underline{E}}arth$ ${\underline{R}}esearch$) is a NASA funded Earth Science REASoN project that strives to provide highly accurate, carefully calibrated, long-term climate data records and near-real-time ocean products suitable for the most demanding Earth research applications via easy-to-use display and data access tools. A key element of DISCOVER is the merging of data from the multiple sensors on multiple platforms into geophysical data sets consistent in both time and space. The project is a follow-on to the SSM/I Pathfinder and Passive Microwave ESIP projects which pioneered the simultaneous retrieval of sea surface temperature, surface wind speed, columnar water vapor, cloud liquid water content, and rain rate from SSM/I and TMI observations. The ocean products available through DISCOVER are derived from multi-sensor observations combined into daily products and a consistent multi-decadal climate time series. The DISCOVER team has a strong track record in identifying and removing unexpected sources of systematic error in radiometric measurements, including misspecification of SSM/I pointing geometry, the slightly emissive TMI antenna, and problems with the hot calibration source on AMSR-E. This in-depth experience with inter-calibration is absolutely essential for achieving our objective of merging multi-sensor observations into consistent data sets. Extreme care in satellite inter-calibration and commonality of geophysical algorithms is applied to all sensors. This presentation will introduce the DISCOVER products currently available from the web site, http://www.discover-earth.org and provide examples of the scientific application of both the diurnally corrected optimally interpolated global sea surface temperature product and the 4x-daily global microwave water vapor product.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.319-322
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• 1999

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability. Especially, snow, soil moisture, surface temperature, vegetation and rain are the key parameters which should be observed in the global scale. In this paper, new algorithms for these land surface hydrological parameters have been developed by introducing frequency and polarization dependencies of these parameters in the microwave radiative-transfer equations. The algorithms were applied to the TRMM Microwave Radiometer. (TMI) and validated by using the ground data obtained in the Tibetan Plateau. The estimated snow, soil moisture, surface temperature, water content of vegetation and rain patterns corresponded reasonably to the observed ones.