• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.1
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• pp.43-56
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• 2012

The purpose of this study was to propose management strategies through aesthetic landscape assessments for landscape units in the Han River riparian(HRR) area. First, this research reclassified the HRR into "natural," "artificial," "agricultural," and mixed landscape types and selected 37 representative case areas(about $1km{\times}1km$). This study found 71 landscape units in consideration of topography and land surface classification. Landscape assessment consisted of landscape quality and landscape integration assessment. The criteria for assessing landscape quality were "naturalness," "interest," "uniqueness," and "landscape function." "Landscape quality" was ranked into five grades using a matrix. The landscape integration assessment consisted of an inner integration assessment in each landscape unit and outer integration assessment among landscape units. As a result of the field study, case sites were found to have 4,288 landscape units and an area of $42.8km^2$. The forest area was found to have the most space with $11,580,905m^2$(27.1%), while the wet lands had just $52,348m^2$(0.1%). In the landscape quality assessment, about 30.5% of the total area consisted of landscape units that scored highest in "naturalness". In the landscape integration assessment, about 39.3% of the total area consisted of landscape units which scored highest in "integration", denoting visual interrelation and harmony. The existence of disparities in landscape quality in accordance with the form of the landscaping was determined using a Oneway ANOVA, with "naturalistic" landscaping scoring the highest and "artificial" landscaping scoring lowest. This study may contribute to making the HRR area a more ecologically sound and visually attractive landscape space. It is recommended that the aesthetical and ecological value of the landscape unit should be assessed simultaneously in the future.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.34-47
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• 2009

Rapid urbanization is causing environmental and ecological damage, development thoughtless for the environment, and social and economical issues. It is important to grasp urban growth situations and characteristics, reflect them, and establish a policy for the solution of issues pursuant to urbanization and the sustainable and efficient development of national land. This research aims to be used as basic data in establishing an urban policy by analyzing the situations and characteristics of urban growth for the past 20 years in our entire country rather than an existing district. For this, some urban districts were sampled using a 1980s and 2000s version of land cover map produced by Ministry of Environment, and then pattern analysis for urban growth by administrative district ranks was conducted using GIS and a statistical technique. As a result, the development zone area after 1980s has increased by 2.5 times as compared to that before 1980s, and especially in the farm villages neighboring the national capital region, it has increased by 21.2 times. Special cities and metropolitan cities were developed at the districts being low in altitude, close to the principal road and the major downtown, high in road ratio, and restricted environmentally, ecologically and legally, and were diverted from mountains, forests and grassland to urban land. On the other hand, farm villages neighboring a large city, farm villages neighboring the national capital region, and local farm villages were developed at the districts being high in altitude, far from the principal road and the major downtown, low in road ratio, and not restricted environmentally, ecologically and legally, and were diverted from farmland to urban land. That is, it can be seen that urban development has been actively realized despite the unfavorable topographical conditions in the suburban districts due to lack of available land and various regulations and policies as urban growth around big cities expands.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.66-77
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• 2019

This study investigated the feasibility of wintering evergreen broad-leaf trees in the Incheon coastal area through a climate analysis. The coldest monthly mean air temperature ranged from $-2.9^{\circ}C{\sim}-1.6^{\circ}C$. The warmth index of the coastal area of Incheon ranged from $98.89^{\circ}C{\cdot}month-109.03^{\circ}C{\cdot}month$, while the minimum air temperature year ranged from $-13.9^{\circ}C{\sim}-3.6^{\circ}C$. This proved that the Incheon coastal area was not suitable for evergreen broad-leaf trees to grow as the warmth index ranges from $101.0^{\circ}C{\cdot}month{\sim}117.0^{\circ}C{\cdot}month$, and the temperature year-round is $-9.2^{\circ}C$ or higher. This suggests the coastal areas of Incheon is not suitable for the growth of evergreen broad-leaf trees, however some evergreen broad-leaf trees lived in some parts of the area. Wind speed reduction and temperature effect simulations were done using Landschaftsanalyse mit GIS program. As a result of the simulations of wind speed reduction and temperature effects affecting the evergreen broad-leaf trees, it was discovered that a coastal wind velocity of 8.6m/sec was alleviated to be 5m/sec~7m/sec when the wind reached the areas where evergreen broad-leaf trees were present. It was also discovered that species that grew in contact with buildings benefited from a temperature increase of $1.1^{\circ}C{\sim}3.4^{\circ}C$ due to the radiant heat released by the building. Simulation results show that the weather factors affecting the winter growth damages of evergreen broad-leaved trees were wind speed reduction and local warming due to buildings. The wind speed reduction by shielding and local warming effects by buildings have enabled the wintering of evergreen broad-leaved trees. Also, evergreen broad-leaved trees growing in the coastal area of Incheon could be judged to be gradually adapting to low temperatures in winter. This study reached the conclusion that the blockage of wind, and the proximity of buildings, are required for successfully wintering evergreen broad-leaf trees in the coastal area of Incheon.