• Proceedings of the KSRS Conference
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• v.2
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• pp.1027-1030
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• 2006

Development of diurnal warming in the open Okhotsk Sea during the daytime and calm conditions was studied using sea surface temperature (SST) fields retrieved from NOAA AVHRR, Terra and Aqua MODIS, Aqua AMSR-E and ADEOS-II AMSR data. Sea surface wind fields were estimated from AMSR-E/AMSR measurements as well as were obtained from QuikSCAT scatterometer. Weak winds and cloudless conditions were observed in the central area of anticyclone, which moved slowly on 28-30 June 2003 east off Sakhalin. The area where the amplitude of the diurnal SST signal ${\Delta}T$ was significant also shifted slowly and had or circular or elongated shape. The ${\Delta}T$ was estimated relative to the SST values in the areas surrounding the centre of anticyclone where wind speed W exceeded 5- 6 m/s. The diurnal variations of SST, day-night differences were computed using NOAA-12 and NOAA-16 AVHRRderived data. Analysis of simultaneous SST and W fields showed that the increase of W from 0 to 5-6 m/s causes the decrease of ${\Delta}T$ to zero. Maximum warming exceeded $8^{\circ}C$ and was observed in the centre of anticyclone where W = 0 m/s. So strong heating was likely due to the increased chlorophyll a concentration in the area under study that follows from analysis of satellite ocean colour data.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.301-304
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• 2008

Since longer wavelength microwave radiation can penetrate clouds, satellite passive microwave sensors can observe sea ice of the entire polar region on a daily basis. Thus, it is becoming popular to derive sea ice motion vectors from a pair of satellite passive microwave sensor images observed at one or few day interval. Usually, the accuracies of derived vectors are validated by comparing with the position data of drifting buoys. However, the number of buoys for validation is always quite limited compared to a large number of vectors derived from satellite images. In this study, the sea ice motion vectors automatically derived from pairs of AMSR-E 89GHz images (IFOV = 3.5 ${\times}$ 5.9km) by an image-to-image cross correlation were validated by comparing with sea ice motion vectors manually derived from pairs of cloudless MODIS images (IFOV=250 ${\times}$ 250m). Since AMSR-E and MODIS are both on the same Aqua satellite of NASA, the observation time of both sensors are the same. The relative errors of AMSR-E vectors against MODIS vectors were calculated. The accuracy validation has been conducted for 5 scenes. If we accept relative error of less than 30% as correct vectors, 75% to 92% of AMSR-E vectors derived from one scene were correct. On the other hand, the percentage of correct sea ice vectors derived from a pair of SSM/I 85GHz images (IFOV = 15 ${\times}$ 13km) observed nearly simultaneously with one of the AMSR-E images was 46%. The difference of the accuracy between AMSR-E and SSM/I is reflecting the difference of IFOV. The accuracies of H and V polarization were different from scene to scene, which may reflect the difference of sea ice distributions and their snow cover of each scene.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.543-553
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• 2011

Sea ice concentration calculated from the AMSR-E onboard Aqua satellite by using NASA Team2 sea ice algorithm has proven to be very accurate over sea ice in Antarctic Ocean. When glacial ice such as icebergs and ice shelves are dominant in an AMSR-E footprint, the accuracy of the ice concentration calculated from NASA Team2 algorithm is not well maintained due to the different microwave characteristics of the glacial ice from sea ice. We extracted the concentrations of sea ice and glacial ice from two ENVISAT ASAR images of George V coast in southern Antarctica, and compared them with NASA Team2 sea ice concentration. The result showed that the NASA Team2 algorithm underestimates the concentration of glacial ice. To interpret the large deviation of estimation over glacial ice, we analyzed the characteristics of microwave radiation of the glacial ice in PR(polarization ratio), GR(spectral gradient ratio), $PR_R$(rotated PR), and ${\Delta}GR$ domain. We found that glacial ice occupies a unique region in the PR, GR, $PR_R$, and ${\Delta}GR$ domain different from other types of ice such as ice type A, B, and C, and open water. This implies that glacial ice can be added as a new category of ice to the AMSR-E NASA Team2 sea ice algorithm.

• Proceedings of the KSRS Conference
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• v.2
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• pp.1007-1010
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• 2006

This study investigates the spatial structure of the total cloud liquid water content Q fields over the Northwest Pacific Ocean during winter monsoon. The distributions of Q have been estimated from the brightness temperatures of the ocean - atmosphere system $T_B(f)$, where f is frequency, measured by AQUA AMSR-E in January -March 2003. Marine strati (St) and stratocumuli (Sc) are typical for winter monsoon season. They were analysed using mainly high-frequency channel at f = 36.5 GHz, vertical polarisation. $T_B$ data were accompanied by the data on near surface wind speed, air temperature and humidity from the nearest meteorological stations. Tow one-dimensional spectra were computed for downwind and crosswind sections of Q fields. The AMSR-E antenna field of view (14-8 km) and the cloud field sizes (100-1000 km) restricted the spatial scales. The results of case study Jan 31 2003 are presented. Scale-invariant spectrum is typical. In the cases of extended St levels a spectral slope equals about -1.7, conforming to classical -5/3 of turbulence theory. For Sc cases the absolute magnitude of spectral slope is rather higher, as a rule. The value is about -2. In the case when cloud streets are presented, a strait line form of spectrum is less reliable with a slope being rather lower (about -1.4).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.828-830
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• 2003

We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced, to our knowledge, this is the first attempt to process about 10-minute long direct-broadcast data. We modified the processor designed for a granule to process the direct-broadcast data. After the modification, our brightness temperature product differs from the reference by 0.2K rms. Sea surface temperatures are retrieved to demonstrate the utility of AMSR-E.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.349-352
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• 2011

토양수분은 지표와 대기에서 물과 에너지를 교환하는 중요한 수문기상 인자임에도 불구하고 토양수분에 대한 중요성이 부족한 실정이다. 최근에는 위성기술의 발달로 Aqua위성에 탑재된 Advanced Microwave Scanning Radiometer E (AMSR-E)를 이용하여 토양수분을 측정하고 있다. 이는 토양수분을 측정하고 있는 가장 유용한 기기로서 25km의 낮은 공간 해상도를 가지고 있어 토양수분의 변화를 나타내는데 한계점을 가지고 있다. 본 연구에서는 AMSR-E의 공간 해상도를 높이고자 비교적 높은 해상도를 (1km) 가지고 있는 Moderate Resolution Imaging Spectroradiometer (MODIS)를 연동하였으며, MODIS의 산출물 중 Albedo, LST, NDVI 인자를 이용하였다. 이를 바탕으로 1km의 고해상도 일 별 토양수분 지도를 작성하였으며, 이 지도를 각각 관측 토양수분과 비교 검증하였다. 향후 일별 고해상도 토양수분 지도를 작성하면 우리나라에 대한 토양수분 데이터베이스를 구축해 나갈 수 있을 것이다.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.107-107
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• 2011

최근 기후변화로 야기되는 식생의 변화는 수문기상인자인 증발산과 토양수분에 많은 영향을 끼친다. 본 연구의 목적은 식생의 변화가 수문기상인자인 토양수분에 어떠한 영향을 미치는지 분석하고자 하는데 있다. 식생인자와 수문기상 인자와의 상관관계를 알아보기 위해 Moderate Resolution Imaging Spectroradiometer(MODIS) 위성 이미지 데이터를 연구에 적용하였으며, 식생인자는 MODIS 13 Vegetation Indices Product에서 추출한 정규식생지수 Normalized Difference Vegetation Index(NDVI)를 이용하였다. 식생인자와 토양수분의 상관관계를 분석하기 위해 농업기상정보시스템(Rural Development Administration, RDA)에서 측정한 군위, 논산, 옥천, 예산 지역의 토양수분 관측값 및 Aqua 위성에 탑재된 Advanced Microwave Scanning Radiometer E(AMSR-E)를 이용하여 측정한 토양수분 관측값을 MODIS-NDVI와 비교 분석하였다. 식생인자와 수문기상인자의 시계열 자료를 이용하여 변화하는 양상을 알아내고자 하였고 상관성을 분석하여 식생인자가 수문인자에 어떠한 영향을 주는지 파악하였다. 그 결과 RDA 토양수분 관측값은 MODIS-NDVI와 거의 비슷한 경향을 나타남을 확인 할 수 있었으며, 이는 RDA와 AMSR-E의 토양수분의 관측 깊이에 따른 차이로 이 같은 현상이 나타난다고 사료된다, 또한 MODIS-NDVI, AMSR-E, RDA가 가지고 있는 각기 다른 공간 해상도(1km, 25km, point scale)가 반영된 결과라 할 수 있겠다, 추후 이를 보완한다면 보다 식생변화가 토양수분에 미치는 영향분석을 명확히 할 수 있을 것이다.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.47-55
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• 2004

We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced by global data centers, to our knowledge, this is the first attempt to process 10-minute long direct-broadcast (DB) data. We found that the processor designed for a granule needs modification to apply to the DB data. The modification includes the correction to path number, the selection of land mask and the manipulation of dummy scans. Pixel-to-pixel comparison with a reference indicates the difference in brightness temperature of about 0.2 K rms and less than 0.05 K mean. The difference comes from the different length of data between 50-minute granule and about 10-minute DB data. In detail, due to the short data length, DB data do not always have correct cold sky mirror count. The DB processing system is automated to enable the near-real time generation of brightness temperatures within 5 minutes after downlink. Through this work, we would be able to enhance the use of AMSR-E data, thus serving the objective of direct-broadcast.

• Proceedings of the KSRS Conference
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• v.1
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• pp.138-141
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• 2006

In developing algorithms to retrieve the sea surface temperature (SST) and sea surface wind speed from the Advanced Microwave Scanning Radiometer (AMSR) aboard the AQUA and the Advanced Earth Observation Satellite-II (ADEOS-II), data from the SeaWinds aboard ADEOS-II were helpful. Since features of the ocean microwave emission (Tb) related with ocean wind are not well understood, in case of using only AMSR data, combination of AMSR and SeaWinds revealed pronounced features about the ocean Tb. Two results from combinations of the two sensors were shown in this paper. One result was obtained at wind speeds over about 6m/s, in which the ocean Tb varies with the air-sea temperature difference, even though the SeaWinds wind speed is fixed at the same values. The ocean Tb increases as the air-sea temperature difference becomes negative, i.e., the boundary condition becomes unstable. This result indicates that the air temperature should be included in AMSR SST algorithm. The second result was obtained from comparison of two wind speeds between AMSR and SeaWinds. There is a small difference of two wind speeds, which might be related with several mechanisms, such as evaporation and plankton.