• 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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• 2004.10a
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• pp.515-517
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• 2004

Although sustainable development of a city should in theory be based on updated spatial information like land cover/use changes, in practice there are no effective tools to get such information. However the development of satellite and sensor technologies has increased the supply of high resolution satellite data, allowing cost-effective, multi-temporal monitoring. Especially KOMPSAT-1(KOrea Multi-Purpose SATellite) acquired a large number of images of the whole Korean peninsula and covering some large cities a number of times. In this study land-use patterns and trends of Daejeon from the year 2000 to the year 2003 will be considered using land use maps which are generated by manual interpretation of multi-temporal KOMPSAT EOC imagery and to show the possibility of using high resolution satellite remote sensing data for urban analysis.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.331-336
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• 1999

The optical sensors of Electro-Optical Camera (EOC) and Ocean Scanning Multi-spectral Imager (OSMI) aboard the Korea Multi-Purpose SATellite (KOMPSAT) will be placed in a sun synchronous orbit in 1999. The EOC and OSMI sensors are expected to produce the land mapping imagery of Korean territory and the ocean color imagery of world oceans, respectively. Utilization of the EOC and OSMI data would encompass the various fields of science and technology such as land mapping, land use and development, flood monitoring, biological oceanography, fishery, and environmental monitoring. Readiness of data support for user community is thus essential to the success of the KOMPSAT program. As part of testing such readiness prior to the KOMPSAT launch, we have performed the preliminary acceptance test for the KOMPSAT data processing system using the simulated EOC and OSMI data sets. The purpose of this paper is to demonstrate the readiness of the KOMPSAT data processing system, and to help data users understand how the KOMPSAT EOC and OSMI data are processed and archived. Test results demonstrate that all requirements described in the data processing specification have been met, and that the image integrity is maintained for all products. It is however noted that since the product accuracy is limited by the simulated sensor data, any quantitative assessment of image products can not be made until actual KOMPSAT images will be acquired.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1332-1333
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• 2003

• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.357-365
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• 1999

The optical sensors of Electro-Optical Camera (EOC) and Ocean Scanning Multi-spectral Imager (OSMI) aboard the KOrea Multi-Purpose SATellite (KOMPSAT) will be placed in a sun synchronous orbit in late 1999. The EOC and OSMI sensors are expected to produce the land mapping imagery of Korean territory and the ocean color imagery of world oceans, respectively. Utilization of the EOC and OSMI data would encompass the various fields of science and technology such as land mapping, land use and development, flood monitoring, biological oceanography, fishery, and environmental monitoring. Readiness of data support for user community is thus essential to the success of the KOMPSAT program. As a part of testing such readiness prior to the KOMPSAT launch, we have performed the preliminary acceptance test for the KOMPSAT data processing system using the simulated EOC and OSMI data sets. The purpose of this paper is to demonstrate the readiness of the KOMPSAT data processing system, and to help data users understand how the KOMPSAT EOC and OSMI data are processed, archived, and provided. Test results demonstrate that all requirements described in the data processing specification have been met, and that the image integrity is maintained for all products. It is however noted that since the product accuracy is limited by the simulated sensor data, any quantitative assessment of image products can not be made until actual KOMPSAT images will be acquired.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.7-16
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• 2011

This study discussed the applicability of satellite SAR (Synthetic Aperture Radar) imagery with regard to reservoir monitoring, and tried the extraction of reservoir storage from multi-temporal C-band RADARSAT-1 SAR backscattering images of Yedang and Goongpyeong agricultural reservoirs, acquired from May to October 2005. SAR technology has been advanced as a complementary and alternative approach to optical remote sensing and in-situ measurement. Water bodies in SAR imagery represent low brightness induced by low backscattering, and reservoir storage can be derived from the backscatter contrast with the level-area-volume relationship of each reservoir. The threshold segmentation over the routine preprocessing of SAR images such as speckle reduction and low-pass filtering concluded a significant correlation between the SAR-derived reservoir storage and the observation record in spite of the considerable disagreement. The result showed up critical limitations for adopting SAR data to reservoir monitoring as follows: the inappropriate specifications of SAR data, the unreliable rating curve of reservoir, the lack of climatic information such as wind and precipitation, the interruption of inside and neighboring land cover, and so on. Furthermore, better accuracy of SAR-based reservoir monitoring could be expected through different alternatives such as multi-sensor image fusion, water level measurement with altimeters or interferometry, etc.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.4-6
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• 2003

Optical signals from an object may vary at different conditions caused by differences in light source and sensor position. Knowledge of these variations is necessary to enable calibration of the satellite images and confirmation of the sun and sensor angles influences of the spectral signals from the objects. With the use high -resolution Ikonos$^{TM}$ multi-angular images, the bi- directional reflectance effects of mangrove trees were observed when three datasets were compared. The influence of bi- directional reflectance may affect the accuracy of interpreting satellite imagery and obtaining biophysical parameters mangrove and other vegetation by indirect means.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.504-507
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• 2007

The KOMPSAT-2 satellite is a push-broom system with MSC (Multi Spectral Camera) which contains a panchromatic band and four multi-spectral bands covering the spectral range from 450nm to 900nm. The PAN band is composed of six CCD array with 2528 pixels. And the MS band has one CCD array with 3792 pixels. Raw imagery generated from a push-broom sensor contains vertical streaks caused by variability in detector response, variability in lens falloff, pixel area, output amplifiers and especially electrical gain and offset. Relative radiometric calibration is necessary to account for the detector-to-detector non-uniformity in this raw imagery. Non-uniformity correction (NUC) is that the process of performing on-board relative correction of gain and offset for each pixel to improve data compressibility and to reduce banding and streaking from aggregation or re-sampling in the imagery. A relative gain and offset are calculated for each detector using scenes from uniform target area such as a large desert, forest, sea. In the NUC of KOMPSAT-2, The NUC table for each pixel are divided as HF NUC (high frequency NUC) and LF NUC (low frequency NUC) to apply to few restricted facts in the operating system ofKOMPSAT-2. This work presents the algorithm and process of NUC table generation and shows the imagery to compare with and without calibration.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.413-423
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• 2016

Worldview-3 satellite sensor provides panchromatic image with high-spatial resolution and 8-band multispectral images. Therefore, an image-sharpening technique, which sharpens the spatial resolution of multispectral images by using high-spatial resolution panchromatic images, is essential for various applications of Worldview-3 images based on image interpretation and processing. The existing pansharpening algorithms tend to tradeoff between spectral distortion and spatial enhancement. In this study, we applied six pansharpening algorithms to Worldview-3 satellite imagery and assessed the quality of pansharpened images qualitatively and quantitatively. We also analyzed the effects of time lag for each multispectral band during the pansharpening process. Quantitative assessment of pansharpened images was performed by comparing ERGAS (Erreur Relative Globale Adimensionnelle de Synthèse), SAM (Spectral Angle Mapper), Q-index and sCC (spatial Correlation Coefficient) based on real data set. In experiment, quantitative results obtained by MRA (Multi-Resolution Analysis)-based algorithm were better than those by the CS (Component Substitution)-based algorithm. Nevertheless, qualitative quality of spectral information was similar to each other. In addition, images obtained by the CS-based algorithm and by division of two multispectral sensors were shaper in terms of spatial quality than those obtained by the other pansharpening algorithm. Therefore, there is a need to determine a pansharpening method for Worldview-3 images for application to remote sensing data, such as spectral and spatial information-based applications.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1901-1910
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• 2022

Arriving in the new space age, securing technology for fusion application of KOMPSAT-3·3A and global satellite images is becoming more important. In general, multi-sensor satellite images have relative geometric errors due to various external factors at the time of acquisition, degrading the quality of the satellite image outputs. Therefore, we propose a fine-image registration methodology to minimize the relative geometric error between KOMPSAT-3·3A and global satellite images. After selecting the overlapping area between the KOMPSAT-3·3A and foreign satellite images, the spatial resolution between the two images is unified. Subsequently, tie-points are extracted using a hybrid matching method in which feature- and area-based matching methods are combined. Then, fine-image registration is performed through iterative registration based on pyramid images. To evaluate the performance and accuracy of the proposed method, we used KOMPSAT-3·3A, Sentinel-2A, and PlanetScope satellite images acquired over Daejeon city, South Korea. As a result, the average RMSE of the accuracy of the proposed method was derived as 1.2 and 3.59 pixels in Sentinel-2A and PlanetScope images, respectively. Consequently, it is considered that fine-image registration between multi-sensor satellite images can be effectively performed using the proposed method.