• Proceedings of the KSRS Conference
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• v.1
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• pp.479-482
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• 2006

The absorption coefficient and backscattering properties of phytoplankton were calculated from the Mie theory. Given a simple case that phytoplankton and mineral particles are the only constitutions in seawater, the reflectance $b_b({\lambda})/[a({\lambda})+b_b({\lambda})]$was analyzed. Then the chlorophyll concentrations were estimated from remote sensing OC2 algorithm. The results show that reflectance in short wavelength region is more sensitive to the Chl variation; High mineral concentrations in seawater have significant influence on the reflectance spectrum; the existence of high mineral concentration may result in the mistake in chlorophyll estimation from OC2 algorithm.

• Proceedings of the KSRS Conference
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• v.2
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• pp.950-953
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• 2006

SIMP is an international project funded by INTAS aimed at improving the information content, which can be inferred from multi-sensor satellite imagery of marine coastal areas. Scientific teams from Germany, UK, Portugal, and Russia focus on the development of novel tools for marine remote sensing of the coastal zone. In particular, the project teams' benefit from the fact that surface films may enhance the signatures of hydrodynamic processes such as plumes, internal waves, eddies, etc., on microwave, optical, and infrared imagery. The project's objectives are to develop a robust methodology for identifying slick-related phenomena/processes through their surface signatures and thereby, to improve the discrimination capabilities between slicks and other oceanic and atmospheric phenomena by taking into account information gained from satellite imagery quasi-simultaneously recorded at microwave, visible and IR wavelengths. The results of the two project years are summarized. Examples are given for the project’s web presentation, laboratory and field experiments, and of the analyses of various satellite data.

• Proceedings of the KSRS Conference
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• v.1
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• pp.406-408
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• 2006

Various geological thematic maps such as grain size or ground water level maps have been generated by interpolating sparsely sampled ground survey data. When there are sampled data at a limited number of locations, to use secondary information which is correlated to primary variable can help us to estimate the attribute values of the primary variable at unsampled locations. This paper applies two multivariate geostatistical algorithms to integrate remote sensing imagery with sparsely sampled ground survey data for spatial estimation of grain size: simple kriging with local means and kriging with an external drift. High-resolution IKONOS imagery which is well correlated with the grain size is used as secondary information. The algorithms are evaluated from a case study with grain size observations measured at 53 locations in the Baramarae beach of Anmyeondo, Korea. Cross validation based on a one-leave-out approach is used to compare the estimation performance of the two multivariate geostatistical algorithms with that of traditional ordinary kriging.

• Proceedings of the KSRS Conference
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• v.1
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• pp.312-315
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• 2006

Radio occultation technique has been used in planetary science to obtain reliable and accurate temperature profiles of the other planets' atmosphere for decades. It relies on the fact that radio waves are bent and delayed due to the gradient of atmospheric refractivity along-ray-path. With the advent of Global Positioning System (GPS), it becomes possible to retrieve the refractivity and temperature profiles of the Earth's atmosphere from the occultation data. We have developed a retrieval algorithm and compared the results of our algorithm with the data of CHAMP to verify the accuracy of our algorithm is good enough. In our algorithm, there are some smoothing steps when retrieving. We analysis the data of FORMOSAT-3 and compare the results with and without smoothing and the results of TACC to see is there any phenomenon deleted after smoothing.

• Proceedings of the KSRS Conference
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• v.1
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• pp.320-323
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• 2006

Temperature inversion may cause air pollution problems because air pollutants cannot be dissipated through vertical motion of the atmosphere and are accumulated near the surface. The air quality is worsen gradually if an inversion event lasts for a long time. An inversion event is defined as consecutive temperature profiles with occurrence of the temperature inversion condition. In this paper, temperature inversion events over three major cities on Taiwan are analyzed. They are measured by ground-based microwave radiometers installed in Taipei, Taichung, and Kaohsiung from 2002 to 2004 by the Environment Protection Administration (EPA) of Taiwan. Characteristics of temperature inversion events at the three cities are extracted using different classification methods.

• 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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• 2007.03a
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• pp.247-250
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• 2007

다양한 지구관측위성으로부터 획득된 윈격탐사 자료들은 맴핑 환경모니터링, 재난 관리，도심 모니터링등과 같은 다양한 분야의 정보를 생성하고 분석하는데 많은 잠재력을 가지고 있다. 특별히 고해상도 위성영상의 경우 도심 지역의 다양한 정보를 손쉽게 파악이 가능하며， 이를 기반으로 효과적인 도심 관리 및 시설 투자가 이루어 질 수 있다 그러나 이러한 고해상도 위성영상의 경우 공간 해상력은 매우 좋으나분광해상력 측면에서는 많은 한계를 보이고 있는 단점을 가지고 있다 이를 보완하기 위한 방법으로 고해상도 흑백모드영상과 중${\cdot}$ 저해상도 다중분광영상 혹은 초분광영상간 영상 합성기법을 통해 분광 능력의 향상을 도모하는 기법들이 연구되어져 왔으며보다 최적의 결과를 위한 다양한 알고리즘들이 개발되어 왔다 본 연구에서는 이러한 영상융합결과의 향상을 위한 방법으로 객체기반 단위의 영상합성 방법을 제시하였으벽이 결과와 화소기반 영상융합 결과와의 비교${\cdot}$ 분석도 수행해 보았다. 이를 위해 Landsat-7 ETM+ 혹백영상과 Hyperion 초분광영상을 실험대상으로 선정하여 분석하였으벽 대표적인 영상융합방법인 PCA 융합기법을 활용하였다.

• ETRI Journal
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• v.31 no.3
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• pp.348-350
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• 2009

To fit the limited volume and power consumption of the passive radio frequency transmission system of the electronic time fuze, an improved coded mark inversion (CMI) is proposed in this letter. From the performance analysis, the energy transmission efficiency of this encoding method is at least 50% higher than that of CMI and NRZ. Finally, the experiment results show that by adopting this improved CMI, the change of DC voltage through magnetic coupling is lower than 0.2 V when the accuracy of data transmission is above 99.5%.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.119-124
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• 2001

In this pattern recognition on the large volumes of remote sensing satellite images, the inference time is much increased. In the case of the remote sensing data [5] having 4 wavebands, the 778 training patterns are learned. Each land cover pattern is classified by using 159, 900 patterns including the trained patterns. For the fuzzy classification, the 778 fuzzy rules are generated. Each fuzzy rule has 4 fuzzy variables in the condition part. Therefore, high performance parallel fuzzy inference system is needed. In this paper, we propose a novel parallel fuzzy inference system on T3E parallel computer. In this, fuzzy rules are distributed and executed simultaneously. The ONE_To_ALL algorithm is used to broadcast the fuzzy input to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of the fuzzy rules, the parallel fuzzy inference algorithm extracts match parallelism and achieves a good speed factor. This system can be used in a large expert system that ha many inference variables in the condition and the consequent part.

• Spatial Information Research
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• v.2 no.2
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• pp.175-188
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• 1994

A competitive learning network was proposed as unsupervised training method of remote sensing data, Its performance and computational re¬quirements were compared with conventional clustering techniques such as Se¬quential and K - Means. An airborne remote sensing data set was used to study the performance of these classifiers. The proposed algorithm required a little more computational time than the conventional techniques. However, the perform¬ance of competitive learning network algorithm was found to be slightly more than those of Sequential and K - Means clustering techniques.