• Journal of Environmental Science International
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• v.4 no.2
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• pp.169-180
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• 1995

This Daper presents effective simulation of the dispersion of thermal discharge which can be relesed at Boryong power plant. Applied numerical models are finite difference method for hydrodynamic analysis and Masch-model comprised of conditions for ambient current velocity. Application of these models is done in Cheonsu Bay Summing up the results of this study are as follows; 1. It is found that the result for measurements of temperature appears high at southwardly Songdo on flood. The reason is that tidal currents which flowed north direction were accompanied with southwardly dispersed thermal discharge. A minute Particle of thermal Plume has a tendency to dispels inward Deacheon Bay. 2. According to the results of numerical experiment, maximum distance for thermal discharge dispersion appeared 10.8 km at lower part and 8.6 km at upper part with power plant outlet as starting point. 3. Comparative the numerical simulation and Airbone Multispectral Scanner indicated that thermal discharge should be verified separative phenomena. The simulated results were compared with field data set showing good agreement. It is concluded that these model can be simulated well.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.136-139
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• 2004

The extraction of 'end-pixels' (i.e. end-members) aims to quantify the abundance of different materials in a single pixel, which becomes popular in the subpixel analysis for hyperspectral dataset. In this paper, we present a new concept called 'End-Pixel of Features (EPF)' to extends the concept of end-pixels for multispectral data and even panchromatic data. The algorithm combines the advantages of previous simplex and clustering methods to search the EPFs in the feature space and reduce the effects of noise. Some experimental results show that, the proposed methodology can be successfully used to hyperspectral data and other remote sensing data.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.673-676
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• 1998

Future land remote sensing satellite systems will kikely be constrained in terms of communication band-width. To alleviate this limitation, the data must be compressed. Image data obtained from satellite exhibit a high degree of spatial and spectral correlations that must be properly exploited. In this paper we propose multispectral image data compression using wavelet transform and selective predicted vector quantization. Th eproposed method is based on accuratly predicting other band from reference band and reducing bit rate through threshold map. we can achieve better compression effeciency than conventional methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.16-25
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• 1998

In this paper, we propose features extraction method using Rough sets theory for efficient data classifications in hyperspectral environment. First, analyze the properties of multispectral image data, then select the most efficient bands using discemibility of Rough sets theory based on analysis results. The proposed method is applied Landsat TM image data, from this, we verify the equivalence of traditional bands selection method by band features and bands selection method using Rough sets theory that pmposed in this paper. Finally, we present theoretical basis to features extraction in hyperspectral environment.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.724-726
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• 2003

Currently available image fusion methods are not efficient for fusing the Landsat 7 images. Significant color distortion is one of the major problems. In this paper, using the well-known wavelet based method for data fusion between high-resolution panchromatic and low-resolution multispectral satellite images, we performed Landsat 7 image fusion. Based on the experimental results obtained from this study, we analyzed some reasons for color distortion. A new approach using the biorthogonal wavelets based method for data fusion is presented. This new method has reached an optimum fusion result - with the same spectral resolution as the multispectral image and the same spatial resolution as the panchromatic image with minimum artifacts.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.135-143
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• 2000

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-Purpose SATellite (KOMPSAT) to perform global ocean color monitoring for the study of biological oceanography. HOMPSAT was launched 21 December 1999. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance data measured before launch. The radiometric response linearity and dynamic range are analyzed and the dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.226-226
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• 2004

• Proceedings of the Optical Society of Korea Conference
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• 1995.06a
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• pp.53-58
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• 1995

Examples of advanced digital electro-optic imaging systems for the satellite remote sensing applications are introduced including multispectral focal plane assembly for newly proposed 1-m spatial resolution capability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.135-152
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• 2018

The purpose of this study is to propose an optimal fusion method of aerial multi - sensor data to improve the accuracy of land cover classification. Recently, in the fields of environmental impact assessment and land monitoring, high-resolution image data has been acquired for many regions for quantitative land management using aerial multi-sensor, but most of them are used only for the purpose of the project. Hyperspectral sensor data, which is mainly used for land cover classification, has the advantage of high classification accuracy, but it is difficult to classify the accurate land cover state because only the visible and near infrared wavelengths are acquired and of low spatial resolution. Therefore, there is a need for research that can improve the accuracy of land cover classification by fusing hyperspectral sensor data with multispectral sensor and aerial laser sensor data. As a fusion method of aerial multisensor, we proposed a pixel ratio adjustment method, a band accumulation method, and a spectral graph adjustment method. Fusion parameters such as fusion rate, band accumulation, spectral graph expansion ratio were selected according to the fusion method, and the fusion data generation and degree of land cover classification accuracy were calculated by applying incremental changes to the fusion variables. Optimal fusion variables for hyperspectral data, multispectral data and aerial laser data were derived by considering the correlation between land cover classification accuracy and fusion variables.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.471-478
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• 2011

High resolution Pan-sharpening technique is becoming increasingly important in the field of remote sensing image analysis as an essential image processing to improve the spatial resolution of original multispectral image. The general scheme of pan-sharpening technique consists of upsampling process of multispectral image and high-pass detail injection process using the panchromatic image. The upsampling process, however, brings about image blurring, and this lead to spectral distortion in the pan-sharpening process. In order to solve this problem, this paper presents a new method that adopts image restoration techniques based on optimization theory in the pan-sharpening process, and evaluates its efficiency and application possibility. In order to evaluate the effect of image restoration techniques on the pansharpening process, the result obtained using the existing method that used bicubic interpolation were compared visually and quantitatively with the results obtained using image restoration techniques. The quantitative comparison was done using some spectral distortion measures for use to evaluate the quality of pan-sharpened image.