• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.201-203
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• 2004

We present here, some of the studies carried for estimation of rainfall over land and oceanic regions in and around South Korea. We use active and passive microwave measurements from TRMM - TMI and Precipitation Radar (PR) respectively during a typhoon even named - RUSA that took place during 30 Aug. 2002. We have followed due approach by Yao at. all (2002) and examined the performance of their algorithm using two main predictor variable, named as Scattering Index (SI) and Polarization Corrected Brightness Temperature (PCT) while using TMI data. The rainfall rate estimated using PCT and SI shows some under-estimation as compared to the AWS rainfall products from the PR in common area of overlap. A larger database thus would be used in future. To establish a new rain rate algorithm over Korean region based on the present case study.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.76-82
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• 1998

Increase of greenhouse gas due to $CO_2$ and CH$_4$ gases would cause the global warming in the atmosphere. According to the global circulation model, it is pointed out in the Okhotsk Sea that the large increase of atmospheric temperature might be occurredin this region by global warming due to the doubling of greenhouse effectgases. Therefore, it is very important to monitor the sea ice extents in the Okhotsk Sea. To improve the sea ice extents and concentration with more highly accuracy, the field experiments have begun to comparewith Airborne Microwave Radiometer (AMR) and video images installed on the aircraft (Beach-200). The sea ice concentration is generally proportional to the brightness temperature and accurate retrieval of sea ice concentration from the brightness temperature is important because of the sensitivity of multi-channel data with the amount of open water in the sea ice pack. During the field experiments of airborned AMR the multi-frequency data suggest that the sea ice concentration is slightly dependending on the sea ice types since the brightness temperature is different between the thin and small piece of sea ice floes, and a large ice flow with different surface signatures. On the basis of classification of two sea ice types, it is cleary distinguished between the thin ice and the large ice floe in the scatter plot of 36.5 and 89.0GHz, but it does not become to make clear of the scatter plot of 18.7 and 36.5GHz Two algorithms that have been used for deriving sea ice concentrations from airbomed multi-channel data are compared. One is the NASA Team Algorithm and the other is the Bootstrap Algorithm. Intrercomparison on both algorithms with the airborned data and sea ice concentration derived from video images bas shown that the Bootstrap Algorithm is more consistent with the binary maps of video images.

• 대한원격탐사학회지
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• 제15권1호
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• pp.21-30
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• 1999

구름 수액량은 일기예보나 수치예보 모델링 분야에 매우 중요하다. 그리고 중간규모의 기상현상에서 잠열의 크기를 좌우하며, 여러 규모의 기상 관련 모델 시스템을 개발 할 때에도 중요한 요소로 작용한다. 본 연구에서는 GMS-5 자료를 이용하여 구름 수액량을 추정하고, SSM/I 자료와 지상 마이크로복사계에 의한 구름 수액량과 비교하였다. 먼저, 본 연구는 구름알베도와 구름 두께와의 관계를 찾아내고 이 관계를 이용하여 구름 수액량을 계산하였다. 그리고 여기서 구해진 결과를 SSM/I 자료와 지상 마이크로파복사계에 의한 구름 수액량과 비교하였다. GMS-5 자료와 지상 마이크로파복사계에 의한 구름 수액량값의 상관계수는 0.86, RMSE 는 9.23 mg/$cm^2$로 나타났고, SSM/I 자료와의 상관계수는 0.84, RMSE = 14.02 mg/$cm^2$ 이였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.162-162
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• 2020

토양수분은 TDR(Time Domain Reflectometry)이나 Tensiometer 등의 장비를 이용하여 측정을 시행하고 있으나, 이를 위해서는 많은 인력과 경제적 자원이 소비될 뿐만 아니라 시공간적으로 측정할 수 있는 범위에 한계가 있다. 지상 관측의 대안으로 MIRAS(Microwave Imaging Radiometer with Aperture Synthesis)나 SMAP(Soil Moisture Active Passive), AMSR2(Advanced Microwave Scanning Radiometer 2) 등의 수동 마이크로파 위성 센서를 이용한 공간 토양수분 관측이 수행되었으나, 낮은 공간 해상도(9~36km)는 지역 규모의 토양수분 분포를 나타내기 충분하지 않고, 높은 불확실성을 내포하고 있다. 본 연구에서는 금강 상류의 용담댐 유역(930.0㎢)을 대상으로 Sentinel-1 C-band SAR(Synthetic Aperture Radar) 영상을 이용한 토지 피복 및 토양 속성을 고려한 10m 해상도의 토양수분 산출을 수행하였다. 용담댐 유역은 산림 79.7%, 논 9.0%, 밭 5.4%, 주거지 2.9%의 토지 피복 비율을 가지며 토양은 사양토(66.6%)와 양토(20.9%)가 우세하다. Sentinel-1 C-band SAR 영상은 SeNtinel Application Platform(SNAP)을 이용하여 전처리 후, 후방산란계수로 변환하였다. 토양수분 알고리즘은 TU-Wien change detection algorithm과 Regression model을 활용하였고, 검증을 위한 실측 토양수분 자료는 한국수자원공사(K-water)에서 제공하는 5년(2014~2018)간의 토양수분 관측자료를 이용하였다. 산출된 토양수분은 결정계수(Coefficient of determination, R²) 및 평균제곱근오차(Root Mean Square Error, RMSE)를 이용하여 실측 토양수분과 비교하였다. Sentinel-1 C-band SAR 영상을 이용한 고해상도의 토양수분 산출은 토지 피복 및 토양 속성을 고려한 지역 규모의 공간 토양수분 분포 및 시간적 변화를 표현 가능할 것으로 판단된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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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.

• 한국지리정보학회지
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• 제5권2호
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• pp.47-53
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• 2002

본 연구에서는 열대강우관측 위성(TRMM) 자료를 이용하여 해상풍을 예측하였고, TRMM TMI 휘도 온도와 북미 주변의 NDBC (National Data Buoy Centers) 부이 자료를 이용하여 해상풍을 추정하였다. 이 결과는 행렬방정식에 의한 부이와 비교하였는데 RMSE, BIAS 그리고 상관계수는 각각 2.19 $ms^{-1}$, 1.10 $ms^{-1}$, 그리고 0.81로 나타났으며, 이 결과는 앞으로 TRMM TMI를 이용한 해양 연구에 가능성을 보여주었다.

• 대한원격탐사학회지
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• 제20권1호
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.448-453
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• 2002

Remote sensing technology is one of the most powerful tools for human to know the nature and their living environment. However, before microwave remote sensing was developed and applied, remote sensing application was limited strongly by weather and time. Microwave remote sensing technology solves the problem. It makes us to have the capability to acquire information at all time of the day and under all weather condition, and make remote sensing technology be used in more wider area. Microwave remote sensing system include mainly Synthetic Aperture Radar (SAR), Microwave Radiometer, Microwave Scatterometer, and Altimeter (ALT). As SAR can acquire image whose spatial resolution is similar with visible and infrared image, it is paying much attention to and playing a more and more important role in earth observation. In recent year, the development of new SAR technology (multi-band and multi-polarization technology, InSAR technology, D-InSAR technology, and so on) makes SAR remote sensing go to an new stage, and its application area become more and more widely. The first Synthetic Aperture Radar (SAR) in the world appeared in 1960. After that, SAR and its application all developed very fast. Some radar satellites launched and run (include Seasat-A in 1978, ERS-1 in 1991, JERS-1 in 1992, Radarsat in 1995, and so on) promote SAR research and application in world greatly. China began to develop its SAR sensor and research SAR application in 1970s. After more than 30 years' research, it get some important development in sensor development data processing method, and application. Some operational systems have been used and play an important role. This paper will introduce the development of SAR technology and its application in China.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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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.

• 한국수자원학회논문집
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• 제49권5호
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• pp.423-429
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• 2016

본 연구에서는 GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer 2 (AMSR2) 센서의 토양수분 자료를 Land Parameter Retrieval Model (LPRM) 알고리즘을 통해 전처리하여 2014년도 한반도 지점관측 자료와의 비교 분석을 수행, 위성 토양수분 자료의 적합성을 평가하였다. 통계 분석 결과 AMSR2 X-band의 토양수분 자료는 38개의 지점관측 자료와 비교해 0.03의 평균 bias, 0.16의 평균 RMSE의 낮은 오차 수준을 보였으며, 최대상관계수는 0.67로 나타났다. 또한 AMSR2 센서의 ascending, descending 시간대별 위성 토양수분자료 분석과 X, C1, C2-band의 주파수 영역별 위성 토양수분 자료 분석 결과, ascending overpass time 시간대와, X-band 주파수의 토양수분자료가 지점 관측 자료와 더 좋은 상관관계를 보였다. 본 연구의 분석 결과는 한반도에서 최근 문제가 되고 있는 가뭄을 비롯한 각종 재해 분석 시 토양수분의 공간적 분포를 연구하는데 활용 될 수 있을 것으로 기대된다.