• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.797-808
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• 2019

This study evaluated the applicability of spacebourne datasets to the flood analysis in an ungauged watershed where is no discharge measurements. The Duman River basin of North Korea was selected as a target area which was flooded by recent Typhoon Lionrock. Topographical parameters for flood analysis were estimated from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM). GDEM includes the shortcomings of information on river cross-section, and conducted 2 dimensional flood analysis when considering virtual river cross-section and not considering it. As a result of comparative analysis, an error occurs in the inundation area and depth, but when used carefully, it is considered that the satellite image can be used for creating flood hazard map and utilizing information for response and preparation.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.809-831
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• 2011

Sea Surface Temperature (SST) is one of the most important oceanic variables to understand rapidly-changing climate, so that accurate and error-free SST images should be presented in school science textbooks. However, satelliteobserved SST images in the high-school textbooks presented some errors caused by various reasons. This study analyzed 36 satellite images for SST presented in 24 kinds of high-school textbooks (earth science I and II textbooks on the basis of the 7th National Curriculum) for 17 items. This study investigated errors in image processing such as cloud removal, land masking, color bar, geological and time information, and some erroneous expressions related to the fundamental information of satellites. Twenty five pre-service teachers filled out a survey about several problematic satellite images, and their responses were analyzed. As a result, most of the pre-service teachers did not recognize the errors associated with image processing and tended to comprehend the SST errors as real oceanographic phenomena such as sea ice, river outflow, or cold current. Therefore, satellite SST images in the textbooks should be accurately presented by including detailed items suggested in this study.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1013-1027
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• 2021

Images taken with KOMPSAT-3 have additional NIR and PAN bands, as well as RGB regions of the visible ray band, compared to imagestaken with a standard camera. Furthermore, electrical and optical properties must be considered because a wide radius area of approximately 17 km or more is photographed at an altitude of 685 km above the ground. In other words, the camera sensor of KOMPSAT-3 is distorted by each CCD pixel, characteristics of each band,sensitivity and time-dependent change, CCD geometry. In order to solve the distortion, correction of the sensors is essential. In this paper, we propose a method for detecting uniform regions in side-slider-based KOMPSAT-3 images using segment-based noise analysis. After detecting a uniform area with the corresponding algorithm, a correction table was created for each sensor to apply the non-uniformity correction algorithm, and satellite image correction was performed using the created correction table. As a result, the proposed method reduced the distortion of the satellite image,such as vertical noise, compared to the conventional method. The relative radiation accuracy index, which is an index based on mean square error (RA) and an index based on absolute error (RE), wasfound to have a comparative advantage of 0.3 percent and 0.15 percent, respectively, over the conventional method.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.1-18
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• 2022

Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.3
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• pp.103-114
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• 2013

In this study, we established the ortho mosaic imagery on the Korean Peninsula using KOMPSAT-2 images and conducted an accuracy assessment. Rational Polynomial Coefficient(RPC) modeling results were mostly less than 2 pixels except for mountainous regions which was difficult to select a Ground Control Point(GCP). Digital Elevation Model(DEM) which was made using the digital topographic map on the scale of 1:5,000 was used for generating an ortho image. In the case of inaccessible area, the Shuttle Radar Topography Mission(SRTM) DEM was used. Meanwhile, the ortho mosaic image of the Korean Peninsula was produced by each ortho image aggregation and color adjustment. An accuracy analysis for the mosaic image was conducted about a 1m color fusion image. In order to verify a geolocation accuracy, 813 check points which were acquired by field survey in South Korea were used. We found that the maximum error was not to exceed 5m(Root Mean Square Error : RMSE). On the other hand, in the case of inaccessible area, the extracted check points from a reference image were used for accuracy analysis. Approximately 69% of the image has a positional accuracy of less than 3m(RMSE). We found that the seam-line accuracy among neighboring image was very high through visual inspection. However, there were a discrepancy with 1 to 2 pixels at some mountainous regions.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.633-636
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• 2005

An electro-optical camera system consists of many subsystems such as the optics, the detector, and the electronics and so on. They may create variations in the processed image that were not present original scene. The performance analysis of the electro-optical camera system is a mathematical construct that provides an optimum design through appropriate trade off analysis. The SNR(Signal to Noise Ratio) is one of the most important performance for the electro-optical camera system. The SNR analysis shown in this paper is performed based on the practical high resolution satellite camera design. For the purpose of the practical camera design, the analysis assumes that the defined radiance, which is calculated for the Korean peninsula, reached directly to the telescope entrance. In addition, the actual operation concept such as integration time and the normal operation altitude is assumed. This paper compares the SNR analysis results according to the various camera characteristics such as the optics, the detector, and the camera electronics. In detail, the optical characteristics can be split into the focal length, F#, transmittance, and so on. And the system responsivity, the quantum efficiency, the TDI stages, the quantization noise and the analogue noise can be used for the detector and the camera electronics characteristics. Finally this paper suggests the optimum design to apply the practical electro-optical system.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.587-599
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• 2011

As one measure of image interpretability, NIIRS(National Imagery Interpretability Rating Scale) has been used. Unlike MTF(Modulation Transfer Function), SNR(Signal to Noise Ratio), and GSD(Ground Sampling Distance), NIIRS can describe the quality of overall image at user's perspective. NIIRS is observed with human observation directly or estimated by edge analysis. For edge analysis specially manufactured artificial target is used commonly. This target, formed with a tarp of black and white patterns, is deployed on the ground and imaged by the satellite. Due to this, the artificial target-based method needs a big expense and can not be performed often. In this paper, we propose a new edge analysis method that enables to estimate NIIRS accurately. In this method, natural targets available in the image are used and characteristics of the target are considered. For assessment of the algorithm, various experiments were carried out. The results showed that our algorithm can be used as an alternative to the artificial target-based method.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.19-25
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• 2013

Recently, the high-resolution satellite images is used the land cover and status data for the natural resources or environment management very helpful. The SVM algorithm of image processing has been used in various field. However, classification accuracy by SVM algorithm can be changed by various kernel functions and parameters. In this paper, the typical kernel function of the SVM algorithm was applied to the KOMPSAT-2 image and than the result of land cover performed the accuracy analysis using the checkpoint. Also, we carried out the analysis for selected the SVM kernel function from the land cover of the target region. As a result, the polynomial kernel function is demonstrated about the highest overall accuracy of classification. And that we know that the polynomial kernel and RBF kernel function is the best kernel function about each classification category accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.84-95
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• 2011

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1003-1017
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• 2017

Multispectral image data of high spatial resolution is required to obtain correct information on the ground surface. The multispectral image data has lower resolution compared to panchromatic data. PAN-sharpening fusion technique produces the multispectral data with higher resolution of panchromatic image. Recently the object-based approach is more applied to the high spatial resolution data than the conventional pixel-based one. For the object-based image analysis, it is necessary to perform image segmentation that produces the objects of pixel group. Image segmentation can be effectively achieved by the process merging step-by-step two neighboring regions in RAG (Regional Adjacency Graph). In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. This degradation increases variation of pixel values in same area, and results in deteriorating the accuracy of image segmentation. An iterative approach that reduces the difference of pixel values in two neighboring pixels of same area is employed to alleviate variation of pixel values in same area. The size of segmented regions is associated with the quality of image segmentation and is decided by a stopping rue in the merging process. In this study, the image restoration and segmentation was quantitatively evaluated using simulation data and was also applied to the three PAN-sharpened multispectral images of high resolution: Dubaisat-2 data of 1m panchromatic resolution from LA, USA and KOMPSAT3 data of 0.7m panchromatic resolution from Daejeon and Chungcheongnam-do in the Korean peninsula. The experimental results imply that the proposed method can improve analytical accuracy in the application of remote sensing high resolution PAN-sharpened multispectral imagery.