• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.87-96
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• 2022

As part of strengthening energy security and responding to climate change, the government has promoted various renewable energy measures to increase the development of renewable energy facilities. As a result, small-scale solar installations in rural areas have increased rapidly. The number of complaints from local residents is increasing. Therefore, in this study, deep learning technology is applied to high-resolution aerial images on the internet to detect solar power plants installed in rural areas to determine whether or not solar power plants are installed. Specifically, I examined the solar facility detector generated by training the YOLO(You Only Look Once) v2 object detector and looked at its usability. As a result, about 800 pieces of training data showed a high object detection rate of 93%. By constructing such an object detection model, it is expected that it can be utilized for land use monitoring in rural areas, and it can be utilized as a spatial data construction plan for rural areas using technology for detecting small-scale agricultural facilities.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.103-111
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• 2007

The spectral information based image analysis, visual interpretation and automatic classification have been widely carried out so far for remote sensing data processing. Yet recently, many researchers have tried to extract the spatial information which cannot be expressed directly in the image itself. Using the texture and wavelet scheme, we made a wavelet-based texture fusion image which includes the advantages of each scheme. Moreover, using these schemes, we carried out image classification for the urban spatial analysis and the geological structure analysis around the caldera area. These two case studies showed that image classification accuracy of texture image and wavelet-based texture fusion image is better than that of using only raw image. In case of the urban area using high resolution image, as both texture and wavelet based texture fusion image are added to the original image, the classification accuracy is the highest. Because detailed spatial information is applied to the urban area where detail pixel variation is very significant. In case of the geological structure analysis using middle and low resolution image, the images added by only texture image showed the highest classification accuracy. It is interpreted to be necessary to simplify the information such as elevation variation, thermal distribution, on the occasion of analyzing the relatively larger geological structure like a caldera. Therefore, in the image analysis using spatial information, each spatial information analysis method should be carefully selected by considering the characteristics of the satellite images and the purpose of study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1639-1644
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• 2014

SAR satellite can acquire clear imagery regardless of weather and the images are widely used for land management, natural hazard monitoring and many other applications. Automatic image matching technique is necessary for management of a huge amount of SAR data. Nevertheless, it is difficult to assure the accuracy of image matching due to the difference of image-capturing attitude and time. In this paper, we compared performances of MI method, FMT method and SIFT method by applying arbitrary displacement and rotation to TerraSAR-X images and changing resolution of the images. As a result, when the features having specific intensity were distributed well in SAR imagery, MI method could assure 0~2 pixels accuracy even if the images were captured in different geometry. But the accuracy of FMT method was significantly poor for the images having different spatial resolutions and the error was represented by tens or hundreds pixels. Moreover, the ratio of corresponding matching points for SIFT method was only 0~17% and it was difficult for SIFT method to apply to SAR images captured in different geometry.

• Spatial Information Research
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• v.19 no.5
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• pp.1-11
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• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.63-69
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• 2013

Change detection technique is essential to various applications of Very High-Resolution(VHR) satellite imagery and land monitoring. However, change detection accuracy of VHR satellite imagery can be decreased due to various geometrical dissimilarity. In this paper, the existing fusion evaluation indexes were revised and applied to improve VHR imagery based change detection accuracy between multi-temporal images. In addition, appropriate change detection methodology of VHR images are proposed through comparison of general change detection algorithm with cross-sharpened image based change detection algorithm. For these purpose, ERGAS, UIQI and SAM, which were representative fusion evaluation index, were applied to unsupervised change detection, and then, these were compared with CVA based change detection result. Methodologies for minimizing the geometrical error of change detection algorithm are analyzed through evaluation of change detection accuracy corresponding to image fusion method, also. The experimental results are shown that change detection accuracy based on ERGAS index by using cross-sharpened images is higher than these based on other estimation index by using general fused image.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.1
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• pp.157-165
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• 2011

This study is to be used as a fundamental material of rural amenity resources researches, such as excavating, establishing and modifying national agricultural landscape resources, so as to efficiently manage them. It is carried out with targeting traditional Darangyi-Rice terrace which has design factors of agricultural landscape resources. We have set up the standard range with practicable similar standard(Marginal Farmland and Less Favored Areas and etc), those of Japan, and the results of analyzing the characteristics of Darangyi-Rice terrace already known. As a result of the field investigation, it has been revealed that a great deal of Darangyi-Rice terrace are being used for not corresponding purposes, or damaged and disappeared. For preserving and well-managing Darangyi-Rice terrace as a rural landscape resource which has rural design factors, it should be advanced detailed and accurate studies on present conditions and changes of Darangyi-Rice terrace, with researches on significances, values, utilities and economical efficiency of Darangyi-Rice terrace by regions. In addition, we utilized various spatial imagery data in the researching process. Consequently, it is concluded that if high resolution imagery data is used, it can establish rather minute and accurate large-scale DB, and monitor elaborate changes as well. It is therefore thought that its application can be higher as actualizing DB hereafter.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.401-410
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• 2013

Due to the increasing need for spatial information, there have been a lot of research related with monitoring and revision of changed regions for the acquisition of the accurate and latest information. In this paper, the optimal monitoring management plan for changed regions with respect to the revision periods was proposed. For this purpose, the representative monitoring methods, which are based on database, professional manpower and crowdsourcing of continuous revision, and aerial imagery, satellite imagery and LiDAR of cyclic revision, were investigated. Then, the properties and application status of monitoring systems in Korea were illustrated according to the methods. Finally, the optimal monitoring management plan for continuous and cyclic revisions was suggested through the comparison of properties and revisionable objects of each method. From the result, it was shown to be appropriate for the optimal monitoring management plan of continuous revision as using Internet-Architectural Information System (e-AIS) database cooperated with professional manpower and crowdsourcing, and cyclic revision as using domestic high-resolution satellite images and LiDAR data processed semi-automatically.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.512-514
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• 2004

The Electro-Optical Camera (EOC) is a high spatial resolution, visible imaging sensor which collects visible image data of the earth's sunlit surface and is the primary payload on KOMPSAT-l. The purpose of the EOC payload is to provide high resolution visible imagery data to support cartography of the Korean Peninsula. The EOC is a push broom-scanned sensor which incorporates a single nadir looking telescope. At the nominal altitude of 685Km with the spacecraft in a nadir pointing attitude, the EOC collects data with a ground sample distance of approximately 6.6 meters and a swath width of around 17Km. The EOC is designed to operate with a duty cycle of up to 2 minutes (contiguous) per orbit over the mission lifetime of 3 years with the functions of programmable gain/offset. The EOC has no pointing mechanism of its own. EOC pointing is accomplished by right and left rolling of the spacecraft, as needed. Under nominal operating conditions, the spacecraft can be rolled to an angle in the range from +/- 15 to 30 degrees to support the collection of stereo data. In this paper, the status of EOC such as temperature, dark calibration, cover operation and thermal control is checked and analyzed by continuously monitored state of health (SOH) data and image data during the mission life of 3 years. The aliveness of EOC and operation continuation beyond mission life is confirmed by the results of the analysis.

• 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.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.787-799
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• 2018

Accurate and effective mapping is critical step to monitor the spatial distribution and change of flood inundated area in large scale flood event. In this study, we try to suggest methods to use low spatial resolution satellite optical imagery for flood mapping, which has high temporal resolution to cover wide geographical area several times per a day. We selected the Sebou watershed flood in Morocco that was occurred in early 2010, in which several hundred $km^2$ area of the Gharb lowland plain was inundated. MODIS daily surface reflectance product was used to detect the flooded area. The study area showed several distinct spectral patterns within the flooded area, which included pure turbid water and turbid water with vegetation. The flooded area was extracted by thresholding on selected band reflectance and water-related spectral indices. Accuracy of these flooding detection methods were assessed by the reference map obtained from Landsat-5 TM image and qualitative interpretation of the flood map derived. Over 90% of accuracies were obtained for three methods except for the NDWI threshold. Two spectral bands of SWIR and red were essential to detect the flooded area and the simple thresholding on these bands was effective to detect the flooded area. NIR band did not play important role to detect the flooded area while it was useful to separate the water-vegetation mixed flooded classes from the purely water surface.