• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.419-431
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• 2009

The core of this study is finding out the efficient band selection or extraction method discovering the optimal spectral bands when applying canonical correlation classifier (CCC) to hyperspectral data. The optimal efficient bands grounded on each separability decision technique are selected using Multispec$^{(C)}$ software developed by Purdue university of USA. Total 6 separability decision techniques are used, which are Divergence, Transformed Divergence, Bhattacharyya, Mean Bhattacharyya, Covariance Bhattacharyya, Noncovariance Bhattacharyya. For feature extraction, PCA transformation and MNF transformation are accomplished by ERDAS Imagine and ENVI software. For the comparison and assessment on the effect of feature selection and feature extraction, land cover classification is performed by CCC. The overall accuracy of CCC using the firstly selected 60 bands is 71.8%, the highest classification accuracy acquired by CCC is 79.0% as the case that executes CCC after appling Noncovariance Bhattacharyya. In conclusion, as a matter of fact, only Noncovariance Bhattacharyya separability decision method was valuable as feature selection algorithm for hyperspectral image classification depended on CCC. The lassification accuracy using other feature selection and extraction algorithms except Divergence rather declined in CCC.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.29-36
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• 2011

Evapotranspiration (ET) from the various surfaces needs to be understood because it is a crucial hydrological factor to grasp interaction between the land surface and the atmosphere. A traditional way of estimating it, which is calculating it empirically using lysimeter and pan evaporation observations, has a limitation that the measurements represent only point values. However, these measurements cannot describe ET because it is easily affected by outer circumstances. Thus, remote sensing technology was applied to estimate spatial distribution of ET. In this study, we estimated major components of energy balance method (i.e. net radiation flux, soil heat flux, sensible heat flux, and latent heat flux) and ET as a map using Mapping Evapo-Transpiration with Internalized Calibration (METRIC) satellite-based image processing model. This model was run using Landsat imagery of Gyeongan watershed in Korea on Feb 1, 2003 and Sep 13, 2006. Basic statistical analyses were also conducted. The estimated mean daily ETs had respectively 22% and 11% of errors with pan evaporation data acquired from the Suwon Weather Station. This result represented similar distribution compared with previous studies and confirmed that the METRIC algorithm had high reliability in the watershed. In addition, ET distribution of each land use type was separately examined. As a result, it was identified that vegetation density had dominant impacts on distribution of ET. Seasonally, ET in a growing season represented significantly higher than in a dormant season due to more active transpiration. The ET maps will be useful to analyze how ET behaves along with the circumstantial conditions; land cover classification, vegetation density, elevation, topography.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.1-16
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• 2017

This study was conducted to analyze the urban heat island(UHI) intensity of South Korea by using Moderate Resolution Imaging Spectroradiometer(MODIS) satellite imagery. For this purpose, the metropolitan area was spatially divided according to land cover classification into urban and non-urban land. From the analysis of land surface temperature(LST) in South Korea in the summer of 2009 which was calculated from MODIS satellite imagery it was determined that the highest temperature recorded nationwide was $36.0^{\circ}C$, lowest $16.2^{\circ}C$, and that the mean was $24.3^{\circ}C$, with a standard deviation of $2.4^{\circ}C$. In order to analyze UHI by cities and counties, UHI intensity was defined as the difference in average temperature between urban and non-urban land, and was calculated through RST1 and RST2. The RST1 calculation showed scattered distribution in areas of high UHI intensity, whereas the RST2 calculation showed that areas of high UHI intensity were concentrated around major cities. In order to find an effective method for analyzing UHI by cities and counties, analysis was conducted of the correlation between the urbanization ratio, number of tropical heat nights, and number of heat-wave days. Although UHI intensity derived through RST1 showed barely any correlation, that derived through RST2 showed significant correlation. The RST2 method is deemed as a more suitable analytical method for measuring the UHI of urban land in cities and counties across the country. In cities and counties with an urbanization ratio of < 20%, the rate of increase for UHI intensity in proportion to increases in urbanization ratio, was very high; whereas this rate gradually declined when the urbanization ratio was > 20%. With an increase of $1^{\circ}C$ in RST2 UHI intensity, the number of tropical heat nights and heat wave days was predicted to increase by approximately five and 0.5, respectively. These results can be used for reference when predicting the effects of increased urbanization on UHI intensity.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.33-49
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• 2000

This research demonstrates the application of GIS to the selection of the waste landfill site through the case study of a urban area. The estimation factors for the suitability analysis of the waste landfill site were determined. The database was built through collection, input, and transformation of data. The recent land cover classification data and NDVI data which were obtained through processing of satellite imagery were incorporated into GIS data as estimation factors. The relative weights of importance among 2nd category estimation factors were determined by the pairwise comparison method. Also relative weights of 1st category estimation factors which are divided into the social-economical factor and the natural environmental factor were combined with those of 2nd category estimation factors. As the results of this case study, the suitability analysis was conducted in accordance with various estimation criteria. The highest suitability index was obtained in the case where we considered the relative weights of 2nd category estimation factors as different in the viewpoint which regards the social economical factor as important.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.66-80
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• 2012

It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• The Korean Journal of Archival Studies
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• no.22
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• pp.115-155
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• 2009

As Korea was merged into Japan, the official documents during Kabo Reform and The Great Han Empire time were handed over to the Government-General of Chosun and reclassified from section based to ministry based. However they had been reclassified before many times. The footprints of reclassification can be found in the classification stamps and warehouse number stamps which remained on the cover of official documents from Kabo Reform to The Great Han Empire. They classified the documents by Section in the classification system of Ministry-Department-Section, stamped and numbered them. It is consistent with the official document classification system in The Great Han Empire, which shows the section based classification was maintained. Although they stamped by Section and numbered the documents, there were differences in sub classification system by Section. In the documents of Land Tax Section, many institutions can be found. The documents of the same year can be found in different group and documents of similar characteristics are classified in the same group. Customs Section and Other Tax Section seemed to number their documents according to the year of documents. However the year and the order of 'i-ro-ha(イロハ) song' does not match. From Kabo Reform to The Great Han Empire the documents were grouped by Section. However they did not have classification rules for the sub units of Section. Therefore, it is not clear if the document grouping of classification stamps can be understood as the original order of official document classification system of The Great Han Empire. However, given the grouping method reflects the document classification system, the sub section classification system of the Great Han Empire can be inferred through the grouping method. In this inference, it is understood that the classification system was divided into two such as 'Section - Counterpart Institution' and 'Section - Document Issuance Year'. The Government-General of Chosun took over the official documents of The Great Han Empire, stored them in the warehouse and marked them with Warehouse Number Stamps. Warehouse Number Stamp contained the Institution that grouped those documents and the documents were stored by warehouse. Although most of the documents on the shelves in each warehouse were arranged by classification stamp number, some of them were mixed and the order of shelves and that of documents did not match. Although they arranged the documents on the shelves and gave the symbols in the order of 'i-ro-ha(イロハ) song', these symbols were not given by the order of number. During the storage of the documents by the Government-General of Chosun, the classification system according to the classification stamps was affected. One characteristic that can be found in warehouse number stamps is that the preservation period on each document group lost the meaning. The preservation period id decided according to the historical and administrative value. However, the warehouse number stamps did not distinguish the documents according to the preservation period and put the documents with different preservation period on one shelf. As Japan merged Korea, The Great Han Empire did not consider the official documents of the Great Han Empire as administrative documents that should be disposed some time later. It considered them as materials to review the old which is necessary for the colonial governance. As the meaning of the documents has been changed from general administrative documents to the materials that they would need to govern the colony, they dealt with all the official documents of The Great Han Empire as the same object regardless of preservation period. The Government-General of Chosun destroyed the classification system of the Great Han Empire which was based on Section and the functions in the Section by reclassifying them according to Ministry when they reclassified the official documents during Kobo Reform and the Great Han Empire in order to utilize them to govern the colony.

• Journal of Korea Water Resources Association
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• v.50 no.6
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• pp.429-440
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• 2017

A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images were analyzed to detect the geographical changes in four different tidal flats in the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from the satellite images, which were used as the input of the temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps extracted from the KOMPSAT images indicate that these multispectral high-resolution satellite data is highly applicable to generate good quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the tidal flat area of Gyeonggi and Jeollabuk provinces was estimated to have changed due to tidal effects, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in Jeollanam province revealed that the social and environmental policies can effectively protect coastal wetlands from degradation. Therefore, monitoring for wetland change using high resolution KOMPSAT is expected to be useful to coastal environment management and policy making.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.653-660
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• 2017

The SCS-CN (Soil Conservation Service-Curve Number) method has been practically applied for estimating the effective precipitation. The CN is used to be determined according to the land use condition based on the US standard. However, there are two distinctive differences between U.S. and Korean land use conditions: mountainous (forest) and rice paddy area that cover more than 70% of the Korean territory. The previous work proposed to use 79 for rice paddy area, regardless of the soil type. Because US SCS's goal was originally to increase crops, the SCS classification standard provides only for woods and there are no criteria to distinguish the wood and forest. To determine the CN for forest, alternatively the U.S. Forest Service criteria have been employed in practice considering hydrologic condition class. In this study, we investigated the change of the forest CN using the observed rainfall - runoff data within the target area. The results indicated that the CN for forest was suitable for HC=1, and the corresponding CNs were redetermined between 54 and 55.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.1-11
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• 2019

With the development of remote sensing sensor technology, it has become possible to acquire satellite images with various spectral information. In particular, since the hyperspectral image is composed of continuous and narrow spectral wavelength, it can be effectively used in various fields such as land cover classification, target detection, and environment monitoring. Change detection techniques using remote sensing data are generally performed through differences of data with same dimensions. Therefore, it has a disadvantage that it is difficult to apply to heterogeneous sensors having different dimensions. In this study, we have developed a change detection method applicable to hyperspectral image and high spat ial resolution satellite image with different dimensions, and confirmed the applicability of the change detection method between heterogeneous images. For the application of the change detection method, the dimension of hyperspectral image was reduced by using correlation analysis and principal component analysis, and the change detection algorithm used CVA. The ROC curve and the AUC were calculated using the reference data for the evaluation of change detection performance. Experimental results show that the change detection performance is higher when using the image generated by adequate dimensionality reduction than the case using the original hyperspectral image.