• Journal of the Korean Institute of Landscape Architecture
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• 제20권3호
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• pp.64-78
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• 1992

In this study, elementary school students of both urban and rural areas as its subjects were asked to draw 'A beautiful landscape' by employing the perspective representation technique, i. e., the Perception Map, and to write down the elements comprising 'A beautiful landscape' in the questionnaire sheets. By doing so, an attempt was made 1) to analyze whether there are differences in perceiving 'A beautiful landscape' according to the differences of the environment in which they were brought up ; and, if there are differences. 2) to identify them ; and based on that , 3) to present basic data for evaluation on landscape, on its preference analysis and for Park Planning. The summary of this study is as follows ; 1) The main elements, elementary school students think, comprising 'A beautiful landscape' are 25 ones such as Sky(7), Sea(2), Water(2), Topography(5), Plants(5), Animals(3), School(1), Rural village(1). The natural elements showing a difference are ; Water fall in urban areas and School landscape in rural areas ; the artificial elements are ; City groups(Structures, Facilities, Necessities, Transportation means and Space) in urban areas and School groups in rural areas. Especially, in case of rural area children, they regard 'Trees' as an essential element to be 'A beautiful landscape' comparing to those in urban areas. 2) According to the analysis result on the correlation between the elements comprising a beautiful rural landscape and a beautiful ruban landscape, the correlation between boys and girls is high, showing the same trend with any difference. In comparison of urban areas with rural areas, there is no difference between natural elements, but in artificial elements(7 groups without family) the correlation is quite low, showing that all comprising elements are not the same between rural schools and cities, between schools within the same areas, and between schools of different areas. 3) In identifying the names of elements comprising 'A beautiful landscape', Back-Du Mountain and Sorak Mountain are shown the highest frequency in the category of mountains. In the names of trees and flowers, the elementary school children are thought to consider the kinds of trees and flowers they can see always at hand, i. e., those in their school ground where they spend most of their day time. 4) In the analysis of the numbers of comprising elements according to the responses in the questionnaire sheets and in the Perception Map, 'less than 10' is the most frequently counted number of comprising elements by individual students regardless of rural and urban differences. When the total frequency is divided by the number of students, the mean score is 6-7 without any differences between rural and urban areas, implying that there are no differences in the expression ability between urban and rural schools. 5) According to the result of classyfying and analysizing the landscape appeared on the Perception Map by similar elements and by similar scenes, 'A beautiful landscape' thought by elementary school children is defined not as a standardized form but as 11 types such as the landscape of fields, the landscape of a sea, the landscape of a rural village, a type where elements are assembled, the landscape of cities, the landscape of a school, the landscape coming out of a imagination, and other landscape. Both rural and urban children all consider the landscape of mountains and field and the landscape where several elements are assembled as a commonly beautiful one. Among the landscapes showing rural and urban differences, it can be analyzed that urban children regard the landscapes of cities, imagination, and waterfalls as something characteristic, while rural children regard the landscape of schools and rural villages as something characteristic.

• The Korean Journal of Nuclear Medicine
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• 제25권2호
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• pp.165-176
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• 1991

The purpose of this study was to assess the ability of quantitative Tl-201 tomography to identify and localize coronary artery disease (CAD). The study population consisted of 41 patients (31 males, 10 females; mean age $55{\pm}7$ yr) including 14 with prior myocardial infarction who underwent both exercise Tl-201 myocardium SPECT and coronary angiography for the evaluation of chest pain. From the short axis and vertical long axis tomograms, stress extent polar maps were generated by Cedars-Sinai Medical Center program, and the % stress defect extent (SDE) was quantified for each coronary artery territory. For the purpose of this study, the coronary circulation was divided into 6 arterial segments, and the "myocardial ischemic score" (MIS) was calculated from the coronary angiogram. Sensitivity for the detection of CAD ($\geq50%$ coronary stenosis by angiography) by angiography) by stress extent polar map was 95% in single vessel disease, and 100% in double and triple vessel deseases. Overall sensitivity was 97%. Sensitivity and specificity for the detection of individual diseased vessels were, respectively, 87% and 90% for the left anterior descending artery (LAD), 36% and 93% for the left circumflex artery (LCX), and 71% and 70% for the right coronary artery (RCA). Concordance for the detection of individual diseased vessels between the coronary angiography and stress polar map was fair for the LAD (kappa=0.70), and RCA (kappa=0.41) lesions, whereas it was poor for the LCX lesions (kappa : 0.32). There were siginificant correlations between the MIS and SDE in LAD (rs=0.56, p=0.0027), and RCA territory (rs=0.60, p=0.0094). No significant correlation was found in LCX territory. When total vascular territories were combined, there was a significant correlation between the MIS and SDE (rs=0.42, p=0.0116). In conclusion, the quantitative analysis of Tl-201 tomograms appears to be accurate for determining the presence and location of CAD.

• Journal of the Korean Association of Geographic Information Studies
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• 제20권1호
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• pp.113-126
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• 2017

This study aimed to quantitatively analyze the trends in environmental research that utilize environmental geospatial information through text mining, one of the big data analysis technologies. The analysis was conducted on a total of 869 papers published in the Republic of Korea, which were collected from the National Digital Science Library (NDSL). On the basis of the classification scheme, the keywords extracted from the papers were recategorized into 10 environmental fields including "general environment", "climate", "air quality", and 20 environmental geospatial information fields including "satellite image", "numerical map", and "disaster". With the recategorized keywords, their frequency levels and time series changes in the collected papers were analyzed, as well as the association rules between keywords. First, the results of frequency analysis showed that "general environment"(40.85%) and "satellite image"(24.87%) had the highest frequency levels among environmental fields and environmental geospatial information fields, respectively. Second, the results of the time series analysis on environmental fields showed that the share of "climate" between 1996 and 2000 was high, but since 2001, that of "general environment" has increased. In terms of environmental geospatial information fields, the demand for "satellite image" was highest throughout the period analyzed, and its utilization share has also gradually increased. Third, a total of 80 correlation rules were generated for environmental fields and environmental geospatial information fields. Among environmental fields, "general environment" generated the highest number of correlation rules (17) with environmental geospatial information fields such as "satellite image" and "digital map".

• Korean Journal of Remote Sensing
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• 제37권6_3호
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• pp.1975-1984
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• 2021

Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

• Journal of the Korean Society of Environmental Restoration Technology
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• 제22권5호
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• pp.1-12
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• 2019

It is important to measure the height of trees as an essential element for assessing the forest health in urban areas. Therefore, an automated method that can measure the height of individual tree as a three-dimensional forest information is needed in an extensive and dense forest. Since airborne LiDAR dataset is easy to analyze the tree height(z-coordinate) of forests, studies on individual tree height measurement could be performed as an assessment forest health. Especially in urban forests, that adversely affected by habitat fragmentation and isolation. So this study was analyzed to measure the height of individual trees for assessing the urban forests health, Furthermore to identify environmental factors that affect forest growth. The survey was conducted in the Mt. Bongseo located in Seobuk-gu. Cheonan-si(Middle Chungcheong Province). We segment the individual trees on coniferous by automatic method using the airborne LiDAR dataset of the two periods (year of 2016 and 2017) and to find out individual tree growth. Segmentation of individual trees was performed by using the watershed algorithm and the local maximum, and the tree growth was determined by the difference of the tree height according to the two periods. After we clarify the relationship between the environmental factors affecting the tree growth. The tree growth of Mt. Bongseo was about 20cm for a year, and it was analyzed to be lower than 23.9cm/year of the growth of the dominant species, Pinus rigida. This may have an adverse effect on the growth of isolated urban forests. It also determined different trees growth according to age, diameter and density class in the stock map, effective soil depth and drainage grade in the soil map. There was a statistically significant positive correlation between the distance to the road and the solar radiation as an environmental factor affecting the tree growth. Since there is less correlation, it is necessary to determine other influencing factors affecting tree growth in urban forests besides anthropogenic influences. This study is the first data for the analysis of segmentation and the growth of the individual tree, and it can be used as a scientific data of the urban forest health assessment and management.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제26권5D호
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• Journal of the Korean Association of Geographic Information Studies
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• 제13권1호
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• pp.62-73
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• 2010

A bird is needed efficient conservation through habitat management, as the representative of an organism to evaluate the steady of complex ecosystem. So, this study will offer the useful basic data for preserving habitat from now on, as presenting a estimating model with the GIS program which selected factors effecting the habitat of a forest-dwelling bird in Changwon. As the resort of the survey, the number of forest-dwelling birds living in the 135 survey sites were 5 order, 15 family, 26 species and 922 individual. Also, as the result of making habitat analysis into a predict model, 'NDVI', 'Distance to valley', 'Distance to mixed forest' and 'Area of field' were significant and they had R-squares of 51.3%. Next, as the resort of researching the accuracy of Model, it was a reasonable prediction, as the correlation coefficient is 0.735 and MAPE is 20.7%, and a predict map of habitat was made with the model. This map could predict species diversity of no investigated areas and could be an useful basic data for preserving habitat, as an on-the-spot survey.

• Korean Journal of Remote Sensing
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• 제36권5_4호
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• pp.1153-1166
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• 2020

The purpose of this study was to analyze the spatial correlation between the heat distribution map of the satellite imaging base and the factors that deepen the heat wave, and to explore the heat concentration area and the space where the risk of future heat wave may increase. The global Moran's I of population, land use, and buildings, which are the causes of heat concentration and heat wave deepening, is found to be high and concentrated in specific spaces. According to the analysis results of local Moran's I, heat concentration areas appeared mainly in large cities such as metropolitan and metropolitan areas, and forests were dominant in areas with relatively low temperatures. Areas with high population growth rates were distributed in the surrounding areas of Gyeonggi-do, Daejeon, and Busan, and the use of land and buildings were concentrated in the metropolitan area and large cities. Analysis by Bivarate Local Moran's I has shown that population growth is high in heat-intensive areas, and that artificial and urban building environments and land use take place. The results of this research can lead to the ranking of heat concentration areas and explore areas with environments where heat concentration is concentrated nationwide and deepens it, so ultimately it is considered to contribute to the establishment of preemptive measures to deal with extreme heat.

• Journal of Broadcast Engineering
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• 제21권6호
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• pp.845-860
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• 2016

This paper proposes a digital watermarking scheme to protect the ownership of the freeview 2D or 3D image such that the viewer watches the image(s) by rendering a arbitrary viewpoint image(s) with the received texture image and its depth image. In this case a viewpoint change attack essentially occurs, even if it is not malicious. In addition some malicious attacks should be considered, which is to remove the embedded watermark information. In this paper, we generate a depth variation map (DVM) to find the locations less sensitive to the viewpoint change. For each LH subband after 3-level 2DDWT for the texture image, the watermarking locations are found by referring the DVM. The method to embed a watermark bit to a pixel uses a linear quantizer whose quantization step is determined according to the energy of the subband. To extract the watermark information, all the possible candidates are first extracted from the attacked image by considering the correlation to the original watermark information. For each bit position, the final extracted bit is determined by a statistical treatment with all the candidates corresponding that position. The proposed method is experimented with various test images for the various attacks and compared to the previous methods to show that the proposed one has excellent performance.

• Journal of Internet Computing and Services
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• 제19권1호
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• pp.49-66
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• 2018

This research explores a value chain structure of VR-AR media including user's perception, uses, and evaluation. The purpose of this research focused on factor analysis and the relationship among user's VR-AR adoption motivations and utilities. This research explores correlation between personal value and using motivation. This study was to identify the value structure of respondent on VR-AR usages based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. This study is based on the analysis of the value chain structure factors that affect VR and AR use behavior (attributes, functional benefits, psychological benefits, use value), 'Hierarchical Value Map' between users' The purpose of the model is to construct a model. For this, 'means-end chain theory' was applied to measure the causal relationship between personal value and VR related use behavior. In order to solve this research problem, 135 people were analyzed through the structured questionnaire using the AR and VR content fitness measure and the second APT laddering, and the use of VR-AR : 1) Functional benefits; 2) Psychological benefits; 3) Means to reach value, 4) Objective value chain structure was identified. The results show that VR users tried to smooth the social life through the new virtual reality audiovisual element, the newness of experience, fun, and pleasure through the departure of reality, vividness of experience, and leading fashion. The AR fitness was a game and a new program, and the value of interacting with other people and the value of 'periwinkle' played an important role through the vividness and peripheral interaction of AR, It was an important choice. The important basic values of users' VR and AR selection were correlated with psychological attributes of interaction with others, achievement, happiness and favorable values.