• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.210-221
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• 2022

In order to promptly respond to disasters, the era of new spaces has opened where satellite images with various characteristics can be used. As the number of satellites in operation at home and abroad increases and the characteristics of satellite sensors vary, it is necessary to find satellite images optimized for disaster types. Disaster types were divided into typhoons, heavy rains, droughts, forest fires, etc., and the optimal satellite images were selected for each type of disaster considering satellite orbits, active/passive sensors, spatial resolution, wavelength bands, and revisit cycles. Each satellite orbit TLE (Two Line Element) information was applied to the SGP4 (Simplified General Perturbations version 4) model to develop a satellite orbit simulation algorithm. The developed algorithm simulated the satellite orbit at 10-second intervals and selected an accurate observation area by considering the angle of incidence of each sensor. The satellite orbit simulation algorithm was applied to the case of Typhoon Mitag in 2019 and compared with the actual satellite list. Through the analyzed results, the time and area of the captured image and the image to be recorded were analyzed within a few seconds to select the optimal satellite image according to the type of disaster. In the future, it is intended to serve as a basis for building a system that can promptly request and secure satellite images in the event of a disaster.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.593-599
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• 2013

China's Mapping Satellite-1, developed by the China Aerospace Science and Technology Corporation (CASC), was launched in three years ago. The data from Mapping Satellite-1 are able to use for efficient surveying and geometric mapping application field. In this paper, we fuse the panchromatic and multispectral images of Changchun area, which are obtained from the Mapping Satellite-1, the one that is the Chinese first transmission-type three-dimensional mapping satellite. The four traditional image fusion methods, which are HPF, Mod.IHS, Panshar and wavelet transform, were used to approach for effectively fusing Mapping Satellite-1 remote sensing data. Subsequently we assess the results with some commonly used methods, which are known a subjective qualitative evaluation and quantitative statistical analysis approach. Consequently, we found that the wavelet transform remote sensing image fusion is the optimal in the degree of distortion, the ability of performance of details and image information availability among four methods. To further understand the optimal methods to fuse Mapping Satellite-1 images, an additional study is necessary.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.29-37
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• 1993

The purpose of this paper is to estimate the attitude and the position of SPOT satellite which are needed in producing DEM(Digital Elevation Model) using SPOT satellite image pairs. DEM extraction is consists of three parts. First part is the modeling of satellite position and atitude, second part is the matching of two images to find corresponding point of them and third part is to calculate the elevation of each point by using the result of the first and second part. For modeling inaccessible area, extended modeling algorithm which removes the GCP(Ground Control Point) most errorneous from the GCPs extracted from map iteratively is proposed According to the experiments using a collinearity equation, the second order polynomials are shown to the optimal for .omega.(pitch), and Zs parameters while the first order ones for .kappa.(yaw) .PHI.(roll), Xs, and Ys parameters. The input images used in this paper are 6000*6000 level 1A panchromatic digital SPOT images of Chungchong-do, Korea. With 30 GCPs, experiments on SPOT images show that the planimetric and altimetric RMS errors are 7.11m and 7.10m, respectively, for test points.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1445-1462
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• 2022

Compact Advanced Satellite 500-4 (CAS500-4), which is scheduled to be launched in 2025, is a mid-resolution satellite with a 5 m resolution developed for wide-area agriculture and forest observation. To utilize satellite images, it is important to establish a precision sensor model and establish accurate geometric information. Previous research reported that a precision sensor model could be automatically established through the process of matching ground control point (GCP) chips and satellite images. Therefore, to improve the geometric accuracy of satellite images, it is necessary to improve the GCP chip matching performance. This paper proposes an improved GCP chip matching scheme for improved precision sensor modeling of mid-resolution satellite images. When using high-resolution GCP chips for matching against mid-resolution satellite images, there are two major issues: handling the resolution difference between GCP chips and satellite images and finding the optimal quantity of GCP chips. To solve these issues, this study compared and analyzed chip matching performances according to various satellite image upsampling factors and various number of chips. RapidEye images with a resolution of 5m were used as mid-resolution satellite images. GCP chips were prepared from aerial orthographic images with a resolution of 0.25 m and satellite orthogonal images with a resolution of 0.5 m. Accuracy analysis was performed using manually extracted reference points. Experiment results show that upsampling factor of two and three significantly improved sensor model accuracy. They also show that the accuracy was maintained with reduced number of GCP chips of around 100. The results of the study confirmed the possibility of applying high-resolution GCP chips for automated precision sensor modeling of mid-resolution satellite images with improved accuracy. It is expected that the results of this study can be used to establish a precise sensor model for CAS500-4.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.133-142
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• 2016

KOMPSAT-3A (KOrea Multi-Purpose SATellite-3A) was launched in March 25 2015 with specification of 0.5 meters resolution panchromatic and four 2.2 meters resolution multi spectral sensors in 12km swath width at nadir. To better understand KOMPSAT-3A positional accuracy, this paper reports a test result on the accuracy of recently released KOMPSAT-3A beta test images. A number of ground points were acquired from 1:1,000 digital topographic maps over the target area for the accuracy validation. First, the original RPCs (Rational Polynomial Coefficients) were validated without any GCPs (Ground Control Points). Then we continued the test by modeling the errors in the image space using shift-only, shift and drift, and the affine model. Ground restitution accuracy was also analyzed even though the across track image pairs do not have optimal convergence angle. The experimental results showed that the shift and drift-based RPCs correction was optimal showing comparable accuracy of less than 1.5 pixels with less GCPs compared to the affine model.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.202-210
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• 2019

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.543-547
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• 2002

In this paper, we introduce a more improved camera modeling method for linear pushbroom images than the method proposed by Orun and Natarajan(ON). ON model shows an accuracy of within 1 pixel if more than 10 ground control points(GCPs) are provided. In general, there is high correlation between platform position and attitude parameters but ON model ignores attitude variation in order to overcome such correlation. We propose a new method that obtains an optimal solution set of parameters without ignoring the attitude variation. We first assume that attitude parameters are constant and estimate platform position's. Then we estimate platform attitude parameters using the values of estimated position parameters. As a result, we can set up an accurate camera model for a linear pushbroom satellite scene. In particular, we can apply the camera model to its surrounding scenes because our model provide sufficient information on satellite's position and attitude not only for a single scene but also for a whole imaging segment. We tested on two images: one with a pixel size 6.6m$\times$6.6m acquired from EOC(Electro Optical Camera), and the other with a pixel size 10m$\times$l0m acquired from SPOT. Our camera model procedures were applied to the images and gave satisfying results. We had obtained the root mean square errors of 0.5 pixel and 0.3 pixel with 25 GCPs and 23 GCPs, respectively.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.409-420
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• 2007

Since 1988, pine wilt disease has spread over rapidly in Korea. It is not easy to detect the damaged pine trees by pine wilt disease from conventional remote sensing skills. Thus, many possibilities were investigated to detect the damaged pines using various kinds of remote sensing data including high spatial resolution satellite image of 2000/2003 IKONOS and 2005 QuickBird, aerial photos, and digital airborne data, too. Time series of B&W aerial photos at the scale of 1:6,000 were used to validate the results. A local maximum filtering was adapted to determine whether the damaged pines could be detected or not at the tree level from high resolution satellite images, and to locate the damaged trees. Several enhancement methods such as NDVI and image transformations were examined to find out the optimal detection method. Considering the mean crown radius of pine trees, local maximum filter with 3 pixels in radius was adapted to detect the damaged trees on IKONOS image. CIR images of 50 cm resolution were taken by PKNU-3(REDLAKE MS4000) sensor. The simulated CIR images with resolutions of 1 m, 2 m, and 4 m were generated to test the possibility of tree detection both in a stereo and a single mode. In conclusion, in order to detect the pine tree damaged by pine wilt disease at a tree level from satellite image, a spatial resolution might be less than 1 m in a single mode and/or 1 m in a stereo mode.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.14-17
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• 2008

KOMPSAT-2 is the seventh high-resolution satellite in the world that provides both 1m panchromatic images and 4m multispectral images of the GSD. It is expected to be used across many different fields including digital mapping, territorial and environmental monitoring. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric data, such as satellite orbits and detailed mapping information. This study aims to generate the DEM and orthoimage by using the stereo images of KOMPSAT-2 and to explore the applicability of geo-spatial information with KOMPSAT-2. In order to ensure generation of DEMs of optimal accuracy, the RPCs data and a suitable number of GCPs were used. The accuracy of DEM generated in this research compared with DEM generated from 1:5,000 digital map. The mean differences between horizontal position of the orthoimage and the digital map data are found to be ${\pm}$3.1m, which is in the range of ${\pm}$3.5m, within the permitted limit of a 1:5,000 digital map. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.