• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5417-5422
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• 2013

This research was performed in order to improve the goodness of fit of paddy rice production forecasting using MODIS images and to find out appropriate explanatory variables in the forecasting model. The aim of this paper is to review the use of satellite images for the survey of paddy rice production in Korea. Many developed countries, including the United States, Australia, and Japan, have been using satellite images to produce agricultural statistics such as crop production, cultivated acreage, etc. The survey accuracy of crop production by using satellite images, however, is not satisfied in practical use. In this paper, we reviewed several methods to increase the survey accuracy of rice production statistics, gained from satellite images. Rice was selected for this study because its cultivated area and production amount could be more easily identified than other crops by using satellite images. The MODIS images were used because they involved more appropriate images to estimate and analyze rice production. This study estimated yield functions by using the NDVIs, gained from paddy rice yields and annual average isothermal lines, and the meteorological variables such as sunshine hours, rainfall, and temperature during ripening stage. As a result of yield function estimation, the goodness of fit(R-squared) for the models was shown from 0.768 to 0.891. In this study, it is noteworthy academically and practically that vegetation index(NDVIs) identified by annual average isothermal lines and meteorological variables are very useful for estimating yield functions.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1517-1526
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• 2021

With the recent global and domestic development of Earth observation satellites, the applications of satellite images have been widened. Research for improving the geometric accuracy of satellite images is being actively carried out. This paper studies the possibility of automated ground control point (GCP) generation for CAS-4 satellite, to be launched in 2025 with the capability of image acquisition at 5 m ground sampling distance (GSD). In particular, this paper focuses to check whether GCP chips with 25 cm GSD established for CAS-1 satellite images can be used for CAS-4 and to check whether optimalspatial resolution for matching between CAS-4 images and GCP chips can be determined to improve matching performance. Experiments were carried out using RapidEye images, which have similar GSD to CAS-4. Original satellite images were upsampled to make satellite images with smaller GSDs. At each GSD level, up-sampled satellite images were matched against GCP chips and precision sensor models were estimated. Results shows that the accuracy of sensor models were improved with images atsmaller GSD compared to the sensor model accuracy established with original images. At 1.25~1.67 m GSD, the accuracy of about 2.4 m was achieved. This finding lead that the possibility of automated GCP extraction and precision ortho-image generation for CAS-4 with improved accuracy.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.34-40
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• 2024

Satellite images from Earth-orbit satellites are widely utilized in both the public sector and commercial industry. To achieve a high-quality satellite image service, satellite operation focuses on accurately transmitting images and information of space to users. In particular, the delivery time from ground system to user is the core factor of the quality of a ground station service. Thus, much development is underway to specifically shorten the time required for distribution to users. In this paper, we introduce an interface design of a ground station to shorten the delivery time from order to distribution, related to the archiving order of satellite images.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.379-390
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• 2008

Due to the increase of the amount of image data, the demand for searching similar images is continuously increasing. Therefore, many researches about the content-based image retrieval (CBIR) are conducted to search similar images effectively. In CBIR, it uses image contents such as color, shape, and texture for more effective retrieval. However, when we apply CBIR to satellite images which are complex and pose the difficulty in using color information, we can have trouble to get a good retrieval result. Since it is difficult to use color information of satellite images, we need image segmentation to use shape information by separating the shape of an object in a satellite image. However, because satellite images are complex, image segmentation is hard and poor image segmentation results in poor retrieval results. In this paper, we propose a new approach to search similar images without image segmentation for satellite images. To do a similarity search without image segmentation, we define a similarity of an image by considering SIFT keypoint descriptors which doesn't require image segmentation. Experimental results show that the proposed approach more effectively searches similar satellite images which are complex and pose the difficulty in using color information.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.167-177
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• 2022

In order to obtain satellite image products using the image transmitted to the ground station after capturing the satellite images, many image pre/post-processing steps are involved. During the pre/post-processing, when converting from level 1R images to level 1G images, geometric correction is essential. An interpolation method necessary for geometric correction is inevitably used, and the quality of the level 1G images is determined according to the accuracy of the interpolation method. Also, it is crucial to speed up the interpolation algorithm by the level processor. In this paper, we proposed a lightweight CNN-based interpolation method required for geometric correction when converting from level 1R to level 1G. The proposed method doubles the resolution of satellite images and constructs a deep learning network with a lightweight deep convolutional neural network for fast processing speed. In addition, a feature map fusion method capable of improving the image quality of multispectral (MS) bands using panchromatic (PAN) band information was proposed. The images obtained through the proposed interpolation method improved by about 0.4 dB for the PAN image and about 4.9 dB for the MS image in the quantitative peak signal-to-noise ratio (PSNR) index compared to the existing deep learning-based interpolation methods. In addition, it was confirmed that the time required to acquire an image that is twice the resolution of the 36,500×36,500 input image based on the PAN image size is improved by about 1.6 times compared to the existing deep learning-based interpolation method.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.19-26
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• 2013

The propose of this study is to analyze the optimum spatial resolution of the urban spatial thermal environment structure and to evaluate of the possibility detection using aerial photographs and thermal satellite images. The proper techniques of the optimum spatial resolution for the urban spatial thermal environment structure were analyzed. Thermal infrared satellite image of Seoul city were used for the change rate of surface temperature variation and suggested to the spatial extent and effects of urban surface characteristics and spatial data was interpreted as regions. To extract the surface temperature, Landsat thermal infrared satellite image compared with an automatic weather station data and in the field of the measured temperature and surface temperature by thermal environment affects, the spatial domain has been verified. The surface temperature of the satellite images to extract after adjusting surface temperature isotherms were constructed. The changes in surface temperature from 2008 to 2012 the average surface temperature observation images of changing areas were divided into space. The results of this study are as follows: Through analysis of satellite imagery, Seoul city surface temperature change due to extraction comfort indices were classified into four grades. The comfort index indicative of the temperature of Gangnam-gu, $23.7{\sim}27.2(^{\circ}C)$ range and Songpagu, a $22.7{\sim}30.6(^{\circ}C)$ respectively, the surface temperature of Yeouido $25.8{\sim}32.6(^{\circ}C)$ were in the range.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.245-250
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• 2004

The classification of the satellite images is basic part in Remote sensing. In classification of the satellite images, class separability feature is very effective accuracy of the images classified. For improving classification accuracy, It is necessary to study classification methode than analysis of class separability feature deciding classification probability. In this study, IKONOS, SPOT 5, Landsat TM, were resampled to sizes 1m grid. Above images were calculated the class separability prior to the step for classification of pixels. The results of the study were valued necessary process in geometric information building. This study help to improve accuracy of classification as feature of class separability in the class through optimizing previous classification steps.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.390-393
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• 2007

KOMPSAT-2, the first Korean high resolution earth observing satellite, continuously acquires high resolution images since July 2006. The quality of satellite images should be geometrically and radiometrically ensured before distribution to users. This study focused on absolute radiometric calibration which is a prerequisite procedure to ensure the radiometric quality of optical satellite images. In this study, we performed reflectance-based vicarious calibration methods on several uniform targets collected through several field campaigns in 2007. The radiative transfer model, MODTRAN, was used to estimate the amount of energy received at the sensor. The energy reached at the sensor are affected by several factors such as reflectance of targets, atmospheric condition, geometry condition between Sun and the sensor, etc. This study proposes the absolute radiometric calibration coefficients of KOMPSAT-2 MSC images combining several types of collected data through field works and tried to compare dynamic range of sensor-detected energy with other commercial high resolution sensors.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.221-224
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• 2010

When the image registration methods which were generally used to the low medium resolution satellite images is applied to the high spatial resolution images, some matching errors or limitations might be occurred because of the local distortions in the images. This paper, therefore, proposed the automatic image-to-image registration of high resolution satellite images using local properties of control points to improve the registration result.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.14-23
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• 2005

This paper proposes a method for matching two different images, especially satellite images. In the general image matching fields, when an image is compared to other image, they may have different properties on the size, contents, brightness, etc. If there is no noise in each image, in other words, they have identical pixel level and unchanged edges, the image matching method will be simple comparison between two images with pixel by pixel. However, in many applications, most of images to be matched should have much different properties. This paper proposes an efficient method for matching satellite images. This method is to match a raw satellite image with GCP chips. From this we can make a geometrically corrected image. The proposed method is based on wavelet transformation, not required any pre-processing such as histogram equalization, analysis of raw image like the traditional methods.