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김영섭 ( Young Seup Kim ),박경원 ( Kyung Won Park ),서애숙 ( Ae Sook Suh ) 大韓遠隔探査學會 2002 大韓遠隔探査學會誌 Vol.18 No.4
복사전달모델과 KOMPSAT-1/OSMI 자료를 이용하여 황사탐지 가능성을 조사하였다. 그리고, 황사탐지를 위한 OSMI의 특성을 파악하기 위하여 OSMI와 SeaWiFS의 자료를 이용하여 공간 분광분석과 채널별 스펙트럼 분석을 실시하고, 또한 에어로솔 광학두께를 상호 비교하였다. OSMI와 SeaWiFS 자료를 이용한 x축 방향의 분광분석 결과, 865nm에서 분광특성이 비슷함을 알 수 있었고, 채널별 스펙트럼 분석에서는 765nm과 865nm에서 SeaWiFS의 결과와 비슷하여 이 밴드에서의 OSMI 자료의 활용 가능성을 확인할 수 있었다. 이들 밴드를 이용하여 산출한 OSMI의 황사탐지 화상은 MODIS에서 얻어진 화상과 비슷함을 알 수 있었다. 황사 때의 광학두께는 약 0.8~1.0으로 나타났다. Radiative transfer model was used to detect the yellow sand using KOMPSAT-1/OSMI data. With OSMI and Sea WiFS data, spectrum analysis for spatial and channel were carried out to investigate the characteristics of sensor for the detection of yellow sand. It was compared and analyzed the optical depth of OSMI and SeaWiFS data. Spectral characteristics of x-axis is similar in 765 and 865nm according to spectral analysis for OSMI and SeaWiFS data. It is considered that band 7 and 8(765 and 865nm) of OSMI is suitable for detecting the yellow sand. Compared the yellow sand images by OSMI and MODIS, the data of OSMI are applicable to monitor the yellow sand phenomena. The optical depth of yellow sand event was about 0.8 with 1.0 maximum.
김영섭(Young Seup Kim),홍기만(Gi Man Hong) 한국지리정보학회 2002 한국지리정보학회지 Vol.5 No.2
Ocean surface wind speed was estimated using TRMM(Tropical Rainfall Measurement Mission) TMI(TRMM Microwave/Imager) data. It is used the TRMM TMI brightness temperature and National Data Buoy Center`s buoy winds speed dataset near North-America to estimate by the algorithm of the ocean surface wind speed retrieval over North America. Comparing with the buoy data by D-matrix equation, the result that RMSE, BIAS, and correlation coefficient are 2.19 ms^-1, 1.10 ms^-1, and 0.81, respectively. Therefore the estimated oceanic surface wind speed by TRMM TMI brightness temperature data show that available to ocean research over upper ocean.
김영섭(Kim Young-seup),홍성근(Hong Sung-kun) 군산대학교 수산과학연구소 1985 水産科學硏究 Vol.- No.1
In order to provide the basic data required for setting up the proper strategies to minimize future marine environmental pollution on Kwangyang bay, the general water quality parameters, circulation pattern and dye study were investigated on January 19, 1984. Although TSS is somewhat high level, most suspended solid seem to composed of the inorganic materials. NH₃-N is also low level compared with that of other coastal areas so that the pollution by the nutrients is not serious yet. While COD is very high level in comparison with the results of other areas. The diffusive capability of this bay is assessed to be medium level.
TRMM-PR/VIRS와 GMS 자료를 이용한 강수량 추정에 관한 연구
김영섭 ( Young Seup Kim ),박경원 ( Kyung Won Park ) 大韓遠隔探査學會 2002 大韓遠隔探査學會誌 Vol.18 No.6
TRMM-PR/VIRS와 GMS 자료를 이용하여 강수량을 추정하였다. 강수량 추정의 검증에는 기상청의 AWS 관측자료를 이용하였다. 본 연구의 강수량 추정 절차는 다음과 같다; l)TRMM-PR 자료와 AWS 자료를 이용하여 Z-R 관계식을 도출한다. 2)Z-R 관계식에 의한 추정치와 VIRS의 TBB 자료를 이용하여 강수량 추정식을 도출한다. 3)새롭게 도출된 식의 VIRS의 TEE 대신 GMS의 TBB 자료를 대입하여 광역의 강수량을 추정한다. Z-R 관계식은 Z=303R(0.72)로 나타났고 상관계수는 0.57이었다. 새롭게 제시된 강수량 추정식에 의한 결과의 상관계수는 0.67, RMSE는 17mm/hr로 나타났다. 강수량 추정식은 집중호우 때 과소추정하는 경향을 보였다. Rainfall estimation was conducted based on TRMM-PR/VIRS and GMS data. AWS rainfall data were used for various validation. General procedure is as follows; 1) Z-R relationship was made by the comparison of TRMM-PR and AWS data. 2) new algorithm was developed by the estimates from Z-R equation and TBB of VIRS. 3) rainfall was estimated through the substitution of GMS data for TBB of VIRS in the newly developed algorithm. Z-R relationship based on TRMM is Z=303R(0.72) with correlation coefficient 0.57. The newly developed algorithm is shown as correlation coefficient 0.67 and RMSE 17mm/hr. New algorithm shows the underestimating tendency in case of heavy rainfall event.