• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.263-275
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• 2010

KOSC(Korea Ocean Satellite Center), the primary operational organization for GOCI(Geostationary Ocean Color Imager), was established in KORDI(Korea Ocean Research & Development Institute). For a stable distribution service of GOCI data, various systems were installed at KOSC as follows: GOCI Data Acquisition System, Image Pre-processing System, GOCI Data Processing System, GOCI Data Distribution System, Data Management System, Total Management & Control System and External Data Exchange System. KOSC distributes the GOCI data 8 times to user at 1-hour intervals during the daytime in near-real time according to the distribution policy. Finally, we introduce the KOSC website for users to search, request and download GOCI data.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.305-312
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• 2003

Remote sensing can provide invisible information in addition to acquire wide-view image data from space. Synthetic Aperture Radar (SAR) transmits microwave to the earth from a satellite and collects the reflected echo from the surface. Interferometric processing of SAR data can detect the subtle land deformation. The information of the surface movement by SAR is useful to monitor the volcanic activity, extended subsidence of urbanized area and the prediction of the earthquake caused by crustal deformation, and it complements the conventional levelling and GPS technique. PSInSAR (Permanent Scatterers Interferometric SAR) is one of interferometric techniques to be applied to practical projects in Japan. In this paper, the projects of land deformation monitoring are shown after the explanations of the PSInSAR principle. Tokai earthquake risk assessment is the first example. PSInSAR detects the subduction of crustal deformation of the adjacent area of new assumed epicenter region of the Tokai Earthquake. The extended subsidence of the urbanized area was implemented by using Japanese satellite data i.e. JERS that has so much data the surrounding of Japan as the archive. We examine the relationship between the geological structure and settlement at Nohbi basin including Nagoya city.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.225-227
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• 2003

Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.

• 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.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.125-127
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• 2004

High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classification can't satisfy high-resolution satellite image's classification precision and produce large data redundancy. Object-oriented information extraction not only depends on spectrum character, but also use geometry and structure information. It can provide an accessible and truly revolutionary approach. Using Beijing Spot 5 high-resolution image and object-oriented classification with the eCognition software, we accomplish the cultures' precise classification. The test areas have five culture types including water, vegetation, road, building and bare lands. We use nearest neighbor classification and appraise the overall classification accuracy. The average of five species reaches 0.90. All of maximum is 1. The standard deviation is less than 0.11. The overall accuracy can reach $95.47\%.$ This method offers a new technology for high-resolution satellite images' available applications in remote sensing culture classification.

• Journal of Sensor Science and Technology
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• v.6 no.2
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• pp.106-114
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• 1997

In this paper, we propose an efficient coding method of remotely sensed satellite image using region classification and interband prediction. This method classifies each pixel vector considering spectral characteristics of satellite image data. Then we perform the classified intraband VQ to remove spatial (intraband) redundancy for a reference band image. To remove interband redundancy effectively, we perform the classified interband prediction for the remaining band images. Experiments on LANDSAT TM satellite image show that coding efficiency of the proposed method is better than that of the conventional Gupta's method.

• Journal of IKEEE
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• v.17 no.4
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• pp.517-524
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• 2013

Stereo matching has been grabbing the attention of researchers because it plays an important role in computer vision, remote sensing and photogrammetry. Although most methods perform well with small size images, experiments applying them to large-scale data sets under uncontrolled conditions are still lacking. In this paper, we present an empirical study on stereo matching for large-scale high-resolution satellite images. A new method is studied to solve the problem of huge size and memory requirement when dealing with large-scale high resolution satellite images. Integrating the tiling technique with the well-known dynamic programming and coarse-to-fine pyramid scheme as well as using memory wisely, the suggested method can be utilized for huge stereo satellite images. Analyzing 350 points from an image of size of 8192 x 8192, disparity results attain an acceptable accuracy with RMS error of 0.5459. Taking the trade-off between computational aspect and accuracy, our method gives an efficient stereo matching for huge satellite image files.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.786-789
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• 2003

The detection of sandstorms and industrial pollutants has been the emphasis of this study. Data obtained from meteorological satellites, NOAA and GMS, have been used for detailed analysis. MODIS and Landsat images are also used for the application of future KOMPSAT- 2. Verification of satellite observations has been made with air pollution data obtained by ground-level monitors. It was found that satellite measurements agree well with concentrations and variations of air pollutants measured on the ground, and that satellite technique is a very useful device for monitoring large-scale air pollution in East Asia. The quantitative analysis of satellite image data on air pollution is the goal in the future studies.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.3
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• pp.181-188
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• 2012

Despite the ecological importance of seagrass beds, their distributional information in Korean coastal waters is insufficient. Therefore, we used hydroacoustic system to collect accurate bathymetry and classification of seagrass, and Kompsat-2 (4 m spatial resolution) image for detection of seagrass beds at Deukryang Bay, Korea. The accuracy of Kompsat-2 image classification was evaluated using hydracoustic survey result using error matrix and Kappa value. The total area of seagrass beds from satellite image classification was underestimated compared to the hydroacoustic survey, estimated 3.9 and $4.5km^2$ from satellite image and hydroacoustic data, respectively. Nonetheless, the accuracy of Kompsat-2 image classification over hydroacoustic-based method showing 90% (Kappa=0.85) for the three class maps (seagrass, unvegetated seawater and aquaculture). The agreement between the satellite image classification and the hydroacoustic result was 77.1% (the seagrass presence/absence map). From our result of satellite image classification, Kompsat-2 image is suitable for mapping seagrass beds with high accuracy and non-destructive method. For more accurate information, more researches with a variety of high-resolution satellite image will be preceded.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.85-89
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• 2007

This paper presents the method to provide a fast service for user in image manipulation such as zooming and panning of huge size high resolution satellite image (e.g. Giga bytes per scene). The proposed technique is based on the hierarchical structure that has 3D-Tiling in horizontal and vertical direction to provide the image service more effectively than 2D-Tiling technique in the past does. The essence of the proposed technique is to create tiles that have optimum level of horizontal as well as vertical direction on the basis of current displaying area which changes as user manipulates huge image. So this technique provides seamless service, and will be very powerful and useful for manipulation of images of huge size without data conversion.