• Korean Journal of Environment and Ecology
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• v.25 no.4
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• pp.516-525
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• 2011

We studied the influence certain environmental factors (proximity of roosting site, roads, and residential areas) have on the spatial distribution of cranes in the Cheorwon, Korea. Using a range finder and GPS, data were collected from January to February 2007 and were subsequently evaluated with ArcGIS. The size of the cranes' wintering habitat was estimated to be 7$76.9km^2$. Five hundred and fifty-five flocks of cranes were observed and detailed distributions were collected. Feeding distribution of the cranes showed clustered distribution, however, no tendencies of spatial autocorrelation were apparent. Adjacent regions with paved roads and residences showed lower densities than other areas. Distances at which paved roads and residential areas induced changes in feeding flock densities were 1500m and 1750m, respectively. Feeding flock density decreased with increased distance from roosting site. Feeding flock density of the two crane species did not increase as distance from roads increased, however, the density of individuals showed a significant increasing tendency with increased distance from roads. In both species, density of feeding flocks and individuals significantly increased with increasing distance from residential areas. In Red-crowned Cranes, the density of feeding flocks and individuals significantly decreased with increasing distance from roosting site, however, in the case of White-naped Cranes, there was an even distribution in density of feeding flocks and individuals.

• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.161-171
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• 2002

It has been known that the accurate estimates of 2-dimensional water quality model parameters are difficult for non-experts due to the complexity of theoretical background and input requirement and complicated inter-relationship between model Parameters. The main goal of this study is to Provide expert system for the optimal estimation of water quality model parameters, which is based on the development of chaining mechanism according to the sensitivity analysis of model parameter interactions and GUI interface system on ArcView Avenue. The selected study area is the 35.3- km main Han river starting from Paldang Dam site to the Point of Indo bridge and the tributary inflows including pollutant data are used for the system application and validation. The estimated main model parameters are 0.367 for transverse dispersion coefficient, 0.074 for and 0.162 for. It also shows that the simulated water quality constituents such as DO and BOD based on the estimated model parameters are well agreed with the observed ones. It can be concluded that the developed GIS-based expert system for water quality model parameter estimation and graphical representation of water quality analysis is useful for the scientific water quality management.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.521-539
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• 2009

This study investigates the time-space characteristics of the road traffic flows in Seoul and the relationship with land use patterns. For the purpose, we analyze the road traffic data collected at 118 observation sites over Seoul City area since 1993. We examine the time-trend of the annual average traffic flows per day during the last fourteen years. Three different trends are revealed: rapid increase during the time period between 1993 and 1997, maintenance same level after sharp decrease between year 1997 and 1998, and gradual decrease after sharp decrease between year 2003 and 2004. The spatial distribution patterns of road traffic flows have also been changed significantly during the period. The traffic flows in the urban center have been declined gradually, while the traffic flows in the boundary area and southern CBDs have increased dramatically. In order to examine the relationship with the changes in the land-use patterns and road traffic flows, we analyze the changes in the spatial distribution patterns of population and industries. We developed three multiple linear regression models to test the relationships between the changes in the land-use variables and road traffic flows.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.4
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• pp.436-443
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• 2019

Lyme disease is a national notifiable infectious disease as of September 2018. The number of cases of Lyme disease has recently been increasing. This study analyzed the epidemiological features and clinical symptoms of domestic and imported. From 2011 to December 31, 2018, of the 119 cases, 48 confirmed cases, 63 probable cases, and 8 suspected cases. 70 cases (58.8%) were reported in Korea and 49 cases (41.2%) of imported. In addition, 91 cases (76.5%) were reported during the summer~autumn season (June~November). In 2017, the highest number of 31 cases. The time needed to make a diagnosis was 2.8±14.7 days for domestic occurrences versus 1.4±4.5 days for those cases that infection occurred imported. Among the clinical symptoms, fever and rash were statistically significant (P<0.001). Clinical trials included early localized 31 cases (52.1%), early disseminated 43 cases (35.3%), and late disseminated 15 cases (12.6%). The estimated regions of infection in Korea were Chungnam 12 cases (17.1%), Gyeonggi 12 cases (17.1%), and Gangwon 8 cases (11.4%), Patient care is also considered to be very important as this disease occurs of all ages. Therefore, the promotion of preventive education and identification of epidemiological features are of paramount importance and should be implemented. The study's findings can be used as basic data for the prevention and management of patients with lyme disease.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.319-330
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• 2015

This study was carried out to predict the optimal growth site and estimate carbon stocks of Quercus acuta, evergreen broad-leaved trees in warm temperate zone according to climate change. The criterion for the optimal site prediction was created by quantification method with quantitative and qualitative data, collected from growth factors of stands and environmental factors of survey sites of 42 plots in Q. acuta by study relationship between growth of tree and site environmental factors. A program for the optimal site prediction was developed by using GIS engine tools. To prediction of the suitable growth site of Quercus acuta, developed program in this study applied to Wando in Jeollanam-do, distributing a various evergreen bread-leaved trees of warm temperate zone. In the results from analysis of the optimal site prediction on Q. acuta, the characteristics of the optimal site showed as follows; site environmental features of class I (the best site class for Q. acuta) was defined as 401 ~ 500 m of altitude, $21{\sim}25^{\circ}$ of slope with above hillside, residual of deposit convex of slope type with west of aspect. The area and carbon stocks of optimal site prediction by class for Q. acuta in classI showed 147.1 ha (2.5%), total 316.5 tC/ha, total $1,161tCO_2/ha/yr$ of class I, 2,703.5 ha (46.3%), total 5,817.4 tC/ha, total $21,331tCO_2/ha/yr$ of class II, 2,845.5 ha (48.6%), total 6,123.0 tC/ha, total $2,845.5tCO_2/ha/yr$ of class III and 153.7 ha (2.6%), total 330.7 tC/ha, total $1,213.7tCO_2/ha/yr$ of class IV.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.311-321
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• 2019

This study was carried out to establish basic data for the development of slow-moving landslide hazard classes. Mountain slopes in slow-moving landslide areas ranged from $11.8^{\circ}$ to $37.0^{\circ}$ with a mean slope of $23.8^{\circ}$. However, the slope inclination of microtopography in slow-moving landslide areas was slightly different, with a mean slope of $23.5^{\circ}$ ($10.7^{\circ}{\sim}41.5^{\circ}$) compared with the mountain slope. There was a significant difference (p < 0.05) between the contour intervals of microtopography and the contour intervals of the slow-moving landslide areas. Among all the slow-moving landslide areas examined, 14 plots (approximately 38.0%) were classified into landslide hazard class I, 6 plots (approximately 16.0%) into landslide hazard class II, 5 plots (approximately 14.0%) into landslide hazard class III and IV, and 16 plots (approximately 43.0%) into landslide hazard class V, whereas 9 plots (approximately 24.0%) fit the no landslide hazard class.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.267-277
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• 2019

Photogrammetry and computer vision are identical in determining the three-dimensional coordinates of images taken with a camera, but the two fields are not directly compatible with each other due to differences in camera lens distortion modeling methods and camera coordinate systems. In general, data processing of drone images is performed by bundle block adjustments using computer vision-based software, and then the plotting of the image is performed by photogrammetry-based software for mapping. In this case, we are faced with the problem of converting the model of camera lens distortions into the formula used in photogrammetry. Therefore, this study described the differences between the coordinate systems and lens distortion models used in photogrammetry and computer vision, and proposed a methodology for converting them. In order to verify the conversion formula of the camera lens distortion models, first, lens distortions were added to the virtual coordinates without lens distortions by using the computer vision-based lens distortion models. Then, the distortion coefficients were determined using photogrammetry-based lens distortion models, and the lens distortions were removed from the photo coordinates and compared with the virtual coordinates without the original distortions. The results showed that the root mean square distance was good within 0.5 pixels. In addition, epipolar images were generated to determine the accuracy by applying lens distortion coefficients for photogrammetry. The calculated root mean square error of y-parallax was found to be within 0.3 pixels.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.233-242
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• 2019

ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

• Korean Journal of Heritage: History & Science
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• v.52 no.1
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• pp.82-89
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• 2019

In this study observation records of the National Natural Environment Survey (2008-2012, 2014-2017) and the Korean Natural History Research Information System (KNHRIS) for the common kestrel (2013-2016) were consulted to determine the correlation of the distribution of kestrels in an area and the area's land use type. Distribution characteristics were studied based on data collected over the last 10 years (2008-2017). Findings show that the common kestrel is widely distributed between 4,407 sites registered in KNHRIS in the period of 2008-2012, 3,899 sites in 2014-2017, and 508 sites in 2013-2016. Relationship analysis was conducted for the altitude and urban planning factors of statistics based on a 2017 GIS check to determine the distribution characteristics. The birds' altitude was confirmed to range from 0 to 1,200 metersck but was most commonly observed at less than 100 meters. Above 200 meters, the rate of occurrence decreased rapidly. The rate of occurrence of the common kestrel was highest in Chungcheongnam-do province, followed by Gyeongsangbuk-do, Kyonggi-do, Jeollanam-do and Jeollabuk-do. As urban areas, green areas, commercial areas, and industrial areas the presence of swere positively correlated with the presence of kestrels, the rate of occurrence of the kestrel was higher in those regions. However, there was no significant relationship between the incidence of kestrels and housing construction or residential areas.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.103-112
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• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.