• Korean Journal of Agricultural Science
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• v.27 no.1
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• pp.5-12
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• 2000

The main purpose of this study is to obtain spatial image information toward forest thinning process in Larix forest stands. Thirteen different alternatives were simulated to visualize on the basis of actual thinning work photos. The options were illustrated as photos produced by photoshop program. Each alternatives were evaluated by forest visitor group with total 244 respondents after reliability test. Spatial images of 13 thinning photos were measured by 12 semantic differential scale as broad -narrow, ordered-tangled, friendly-unfriendly, monotonous-divers, dry-refreshing, relieved -stifling, healthy-sickly, uniform-scattered, dead-alive, opened-closed, bent-straight, and beautiful-ugly. In comparison with thinning stands and natural stands, thinning works were visual improvement effects of spatial images. Seemingly, this trend is due to definite form beauty, straight and clear length form of coniferous forest, As can be expected, slash and downwood were negatively related to improvement effects of spatial images. The 60% ratio of stem/ tree height and 450-950 trees/ha was positive in attraction of spatial images. Results indicate how to conduct forest thinning system for spatial images on Larix forest stands.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.413-422
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• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.451-456
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• 2006

Epipolar images have to be generated to stereo display aerial images or satellite images. Pushbroom sensor is used to acquire high resolution satellite images. These satellite images have curvilinear epipolar lines unlike the epipolar lines of frame images, which are straight lines. The aforementioned fact makes it difficult to generate epipolar images for pushbroom satellite images. If we assume a linear transition of the sensor having constant speed and attitude during image acquisition, we can generate epipolar images based on parallel projection model (20 Affine model). Recent high resolution images are provided with RPC values so that we can exploit these values to generate epipolar images without using ground control points and tie point. This paper provides a procedure based on the parallel projection model for generating epipolar images directly from a stereo IKONOS images, and experimental results.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.218-224
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• 1998

The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• 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 Institute of Interior Design Journal
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• v.21 no.1
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• pp.220-227
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• 2012

After The Ramsar Convention took place in Korea in 2008, public interest in environment heightened, and the government has been allocating its budget for conserving our environment. Therefore, the present study focuses on eco-friendly spatial images particularly shown in ecological museums in Korea which recognizes the value of the environment and the ecology and tries to both protect them and alert people about it. The purpose of this study is proving what consist of eco-friendly spatial images by analyzing the expressive word of eco-friendly images and the image of space, providing a basic data for future space planning of ecological museums. To do this, the present study proceeds in three steps. First of all, the base of research in analyzing stage is firmly established by grasping general theories and terms regarding spatial image. As a second step, the composition and the characteristics of exhibition is clarified through on-spot investigation to provide comparative data for spatial image assessment in the future. Also through this step, we could understand how the exhibits are designed currently. In the last stage of research, expressive words regarding eco-friendly spatial images are extracted and used to analyze the spatial image of ecological museums. And the following three conclusions is deduced. First, the expressive words of eco-friendly spatial image that are extracted are as following: "healthy", "coexisting", "clean", "blending", "warm", "soft", "lively", "pure", "cool", "fresh ", "comfortable", "relaxed", "mild", "free", "harmonious", and "healing". As the second conclusion, color, and material, the formation which is an architectural factor did not have a great impact on forming eco-friendly image, but the color and the material did. The third conclusion was that the display with natural aspects actively utilized increased eco-friendly spatial image.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.669-678
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• 2023

Recently, spatial information has been applied to various fields and its usability is increasing day by day. In particular, in the field of civil engineering and construction, BIM based on spatial information is being applied to all construction industries and related research has been conducted. BIM is a technology that utilizes spatial information from the design phase and aids in the construction and maintenance of buildings, including the management of their attributes. However, to apply BIM technology to existing buildings, it takes a lot of time and money to produce models based on design drawings along with current surveying. In this study, quantitative and qualitative analysis was conducted to determine the applicability of the acquired data and the applicability of BIM by generating data and analyzing the accuracy using UAV images and ground lidar, which are representative spatial information acquisition methods. Quantitative analysis revealed that TLS (Terrestrial Laser Scanner) showed reliable accuracy in both planar and elevation measurements, whereas unmanned aerial images exhibited lower accuracy in elevation measurements, resulting in reduced reliability. Qualitative analysis indicated that neither TLS nor unmanned aerial images alone provided perfect completeness. However, the combination of both spatial information sources, tailored to specific needs, resulted in the most comprehensive completeness. Therefore, it is concluded that the appropriate utilization of spatial information acquired through unmanned aerial images and TLS holds the potential for application in the fields of BIM and reverse engineering.

• Current Optics and Photonics
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• v.4 no.6
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• pp.530-539
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• 2020

Hyperspectral images feature a relatively narrow band and are easily disturbed by noise. Accurate estimation of the types and parameters of noise in hyperspectral images can provide prior knowledge for subsequent image processing. Existing hyperspectral-noise estimation methods often pay more attention to the use of spectral information while ignoring the spatial information of hyperspectral images. To evaluate the noise in hyperspectral images more accurately, we have proposed a spectral-spatial cooperative noise-evaluation method. First, the feature of spatial information was extracted by Gabor-filter and K-means algorithms. Then, texture edges were extracted by the Otsu threshold algorithm, and homogeneous image blocks were automatically separated. After that, signal and noise values for each pixel in homogeneous blocks were split with a multiple-linear-regression model. By experiments with both simulated and real hyperspectral images, the proposed method was demonstrated to be effective and accurate, and the composition of the hyperspectral image was verified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.439-448
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• 2022

MV (Moving Vehicle) detection using satellite imagery is important for traffic monitoring and provides a wide range of observations. Specifically, MV detection methods utilizing the time lag in single-pass optical satellite images have been studied for detecting MVs from a single set of images. Because of limitations in detecting MVs outside of roads, most previous studies required road information to limit the moving object to cars on the road. However, it is difficult to obtain road information from inaccessible areas. Therefore, this study proposed a new method for detecting MVs regardless of their locations from single-pass optical satellite images without using additional data. WV-3 (Worldview-3) satellite images were used, and a spatial correlation coefficient map was proposed to detect spatial displacement which denotes MVs across two WV-3 MS images. Finally, evaluation was performed through quantitative metrics and visual inspection. The evaluation results revealed that the proposed method can detect MV movements from the single-pass satellite images. On the contrary, misdetected or undetected MVs due to radiometric differences between the images could be identified by visual inspection. The performance of the proposed method can be improved by minimizing radiometric variations and adding conditions that are robust to radiometric differences between the images.