• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.71-77
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• 2006

MSAS satellite is the geostationary satellite for realizing WADGPS that can get the position of moving object in a wide area receiving the correction signal created from a ground using satellite. In this study, we analyzed two different data. One is using the correction signal transmitted from MTSAT-2 satellite of MSAS and the other is receiving the data of DGPS using BEACON receiver. As we compared both data, we could get the conclusion that the position accuracy of both data is also can get up to the standard or the conventional real-time code DGPS. As a result, we can expect that if we use MTSAT-2 satellite and BEACON receiver together, we can apply them LBS part that require real-time data or the obtaining geospatial information that does not require high accuracy much regardless of topography.

• Proceedings of the KSRS Conference
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• v.2
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• pp.651-654
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• 2006

Infrared channels of newly launched Japanese geostationary satellite, MTSAT-1R are compared with well calibrated MODIS/Terra infrared measurements at 3.7, 6.7, 11, 12 ${\mu}m$ bands. There are four steps in this intercalibration method: 1) data collection, 2) spectral response function correction, 3) data collocation, and 4) calculation of mean bias and conversion coefficients. In order to minimize the navigation error of MTSAT-1R, comparisons are made over the area in which the viewing angle of MTSAT-1R is less than 50$^{\circ}$. The calibration method was tested for August 2005 and within the 40$^{\circ}N$-40$^{\circ}S$, 100$^{\circ}$E-180$^{\circ}$E domain. The differences of spectral response functions were corrected through radiative transfer model simulation. Constructing collocated data differences in viewing geometry, observation time and space were taken into account. In order to avoid the radiance variation induced by cloud presence, clear-sky targets are selected as intercalibration target. The mean biases of 11, 12, 6.7, and 3.7 ${\mu}m$ bands are about -0.16, 0.36, 1.31, and -6.69 K, suggesting that accuracies of 3.7 ${\mu}m$ is questionable while other channels are comparable to MODIS

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.465-474
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• 2010

Real-time rainfall monitoring is of great practical importance over the highly populated Indochina area, which is prone to natural disasters, in particular in association with rainfall. With the goal of d etermining near real-time half-hourlyrain estimates from satellite, the three-layer, artificial neural networks (ANN) approach was used to train the brightness temperatures at 6.7, 11, and $12-{\mu}m$ channels of the Japanese geostationary satellite MTSAT against passive microwavebased rain rates from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and TRMM Precipitation Radar (PR) data for the June-September 2005 period. The developed model was applied to the MTSAT data for the June-September 2006 period. The results demonstrate that the developed algorithm is comparable to the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) results and can be used for flood monitoring across the Indochina area on a half-hourly time scale.

• Proceedings of the KSRS Conference
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• v.1
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• pp.286-289
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• 2006

This paper analyzed the JPEG compression performance of MTSAT-1R(Multi-functional Transport Satellite - 1 Replacement), which is offering the LRIT/HRIT(Low Rate Information Transmissio / High Rate Information Transmission) service now, in order to design the system regarding LRIT/HRIT of COMS(Communication, Ocean and Meteorological Satellite). To do so, we analysed Lossy and Lossless JPEG compression performance regarding the MTSAT-1R LRIT/HRIT data for 10 days, and made comparison to the image characteristics, and understood the JPEG compression characteristics regarding JPEG compression of geostationary meteorological satellite. This result of compression performance analysis is expected to be a reference not only to the system design and realization of COMS LRIT/HRIT but also to those who develop other meteorological satellite receiving systems.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.394-397
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• 2006

본 논문에서는 일본의 정지궤도 위성인 MTSAT(Multi-functional Transport Satellite)-1R의 HRIT/LRIT(High Rate Information Transmission/Low Rate Information Transmission) 데이터의 특성 및 오차를 분석하였다. HRIT/LRIT 데이터를 수신하여 영상을 추출하고, 추출한 영상에 ITU(International Telecommunication Union)의 Space Radiocommunications Stations(이하 SDS) CD에 있는 Map 데이터를 겹쳐서 실제 해안선과의 차이를 계산하였다. 분석을 위하여 10일간의 HRIT/LRIT 수신 데이터를 사용하였고 분석한 결과 MTSAT-1R 위성의 HRIT VIS 영상의 평균오차는 Line 4.42 Pixel, Column 0.66 Pixel, LRIT IR1 영상의 평균오차는 Line 1.05 Pixel, Column 0.19 Pixel인 것을 알 수 있었다.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.271-276
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• 2007

지표면의 파장별 방출율을 알고 있다는 가정하에 대기의 흡수효과가 상이한 두 파장역을 이용하여 대기효과를 보정해주는 일반적인 분리대기창(Generalized Split-Window) 방법으로 MTSAT-1R 자료로부터 지표면 온도(LST) 산출 알고리즘을 개발하였다. 지표면온도 산출 회귀식은 대기복사전달모델 MODTRAN4.0으로 위성으로부터 LST를 산출하는데 영향을 주는 여러 가지 요소(주/야간，수증기, 방출율，위성관측각 등)들을 고려하여 모의된 자료로부터 도출하였다. 개발한 LST 산출알고리즘의 수준을 분석하기 위해 MSGl SEVIRI 센서에 적합하도록 개 발된 Sobrino and Romaguera(2004)의 알고리즘과 GMS-5 VISSR 센서에 적합하도록 개발된 Prata and Cechet(1999)의 알고리즘과 비교하였다. 3 알고리즘을 MTSAT-1R 자료에 적용하여 LST를 산출한 결과 LST의 공간분포는 정성적으로 서로 유사하게 나타났으나，정량적으로는 지리적 위치，계절 및 주간/야간에 따라서 LST가 다르게 나타났다.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.426-429
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• 2008

In this study, we propose the calibration algorithm for the solar channel (550 ${\sim}$ 900 nm) of MTSAT 1R which is the Japanese geostationary satellite launched on 26 Feb. 2005 and located at $140^{\circ}E$. We developed a method utilizing MODIS-derived BRDFs for the solar channel calibration over the bright desert area. Targets are selected based on the desert's brightness, spatial uniformity, temporal stability and spectral stability. The 6S model has been incorporated to account for directional effects of the surface using MODIS-derived BRDF parameters within the spectral interval in interest. Results based on the analysis for the period from November 2007 to June 2008 suggest that MTSAT-1R solar channel measurements have a low bias within 5%.

• Aerospace Engineering and Technology
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• v.6 no.2
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• pp.219-228
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• 2007

The test is performed to measure the accuracy of landmark matching process considering cloud detection performance and to analyze the evolution of this accuracy with respect to the cloud detection processing parameters. For the purpose, MTSAT-1R HiRiD data were used to induce final results. The test result shows that landmarks matching performance estimation on MTSAT-1R HiRiD data is considered as being between 0.06 and 0.09 IR pixel, corresponding to $7{\mu}rad$ and $10{\mu}rad$.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.463-468
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• 2006

This paper analyzed the JPEG compression performance of MTSAT-lR (Multi-functional Transport Satellite-1 Replacement), which is offering the LRIT/HRIT (Low Rate Information Transmissio/High Rate Information Transmission) service now, in order to design the system regarding LRIT/HRIT of COMS (Communication, Ocean and Meteorological Satellite). To do so, we analysed Lossy and Lossless JPEG compression performance regarding the MTSAT-1R LRIT/HRIT data for 10 days, and made comparison to the image characteristics, and understood the JPEG compression characteristics regarding JPEG compression of geostationary meteorological satellite. This result of compression performance analysis is expected to be a reference not only to the system design and realization of COMS LRIT/HRIT but also to those who develop other meteorological satellite receiving systems.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.554-556
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• 2005

Meteorological imager on the Multi-functional Transport Satellite (MTSAT-IR), which has been operating formally since 28 June 2005, was intercalibrated with a polar orbit satellite [Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS)] as a well-calibrated instrument. The intercalibration method used in this study was developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS). This was done for the infrared window channels. The differences of MTSAT-IR and MODIS were are -0.26 K for $11\;\mu m-IR$ window channel, 0.40 K for $12\;\mu m-IR$, window channel, and -0.67 K for $6.7\;\mu m-water$ vapor channel.