• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.4
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• pp.106-127
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• 2010

Although multi-layer planting methods are more widely used as a method for clustered planting and environmental programs such as plant remediation, difficulties have been faced in applying those to planting design. This study develops a basic planting model that can be applied to multi-layer planting in basis on an analysis of forest structures in the Seoul area. An optimal number of clusters was determined through the ISA (Indicator Species Analysis), and 7 basic clusters were found through a cluster analysis by using PC ORD 4.0 software specifically developed for ecological analysis. The 7 basic clusters include the following communities: the Quercus acutissima Community, Sorbus alnifolia-Quercus mongolica Community, Pinus rigida-Pinus densifiora Community, Rododendron mucronulatum var. mucronulatum-Quercus mongolica Community, Juniperus rigida-Quercus mongolica Community, Rododendron mucronulatum var. mucronulatum-Pinus densiflora Community, and Rododendron sclippenbachii-Quercus mongolica Community. The study also selected 57 species with at least a 10% frequency among the plant species existing in the Seoul area and suggested both a companion species and available similar alternative species by conducting an additional interspecific association analysis. This study may help to enhance usefulness of the model in architectural planting design. In addition, the two results named above were synthesized to develop a multi-layer planting model that can be utilized in landscape planting design by selecting similar alternative species through the interspecific association analysis, which includes 7 clusters of natural plants. The multi-layer planting model can be widely applied to design planting because the model has an average target cover range based on the average value of a transformed likelihood.

• Korean Journal of Environment and Ecology
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• v.27 no.5
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• pp.614-624
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• 2013

The purpose of this study is to offer the raw data for establishing the plan of disaster prevention and the continuous conservation of soil ecosystem by grasping the potential soil loss and the danger of erosion using RUSLE method on whole districts in Gyeongju National Park, Korea. In the results of the average amount of soil erosion for the year, the average of all districts was 5.7 ton/ha in annual, and Namsan district was the highest in 7.6 ton/ha in annual and Seoak district was the lowest in 2.1 ton/ha in annual. The dangerous district due to the soil erosion was analyzed as under 1%, and Gumisan and Hwarange district was not serious. But Namsan district was higher than others, especially, there was intensive in all over Geumohbong. Therefore, to protect the all over Geumohbong, we will establish the valid of restoration and management. The types of land cover in Gyeongju National Park mostly showed forest, and as the average amount of soil erosion in forest was 3.7 ton/ha in annual, there was good condition. In the results of the amount of soil erosion due to landform, the deep canyon showed as 7.3 ton/ha in annual per unit area, secondly, the U-shaped valley was analyzed as 6.1 ton/ha in annual. The plain and high ridge were predicted that there occurred the small amount of soil erosion. In future, if we will analyze the amount of soil erosion in Korean National Parks, we will offer the help to establishing the plan of conservation and restoration on soil ecosystem in whole National Parks.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.213-223
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• 2022

This study was conducted to establish a Habitat Suitability index (HSI) based on literature research and field surveys on ecology and habitat of 'Hynobius leechii'. And this study will be used as basic data for qualitative evaluation of habitat environment. The survey sites were divided into natural habitats close to the prototype habitat and artificial restoration areas where Hynobius leechii was monitored. So the types of habitats were diversified. Hynobius leechii is a vulnerable species to climate change because it is affected by the microhabitat and has low mobility. HSI variables of Hynobius leechii were extracted through domestic and overseas literature, and standards were extracted from literature research and field survey. The standards were presented as a value of the physical allowable category in consideration of realization. To verify the study, an in-depth consultation was conducted by amphibians experts. HSI variables of Hynobius leechii were included 9 variables such as Overstory canopy cover(%), Understory cover(%), Water-pH, Soil-pH, Soil relative humidity(%), Leaf litter depth(cm), Rock substrates (%), Type of Coarse woody, Distance from Street or Pollutant(m).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.89-97
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• 2006

Soil erosion has caused serious environmental problems which threaten the foundation of natural resources. In this paper, we chose RUSLE erosion model, which could be connected easily with GSIS and available generally in mid-scale watershed among soil erosion models, and extracted factors entered model by using GSIS spatial analysis method. First, this study used GIS database as soil map, DEM, land cover map and rainfall data of typhoon Memi (2003) to analyze soil loss amount of Dam basin. To analyze the changes of soil loss in considering basin characteristics as up-, mid- and downstream, this study calculated soil erodibility factor (K), topographic factors (LS), and cover management factor (C). As a result of analysis, K and LS factors of upstream showed much higher than those of downstream because of the high ratio of forest. But C factor of downstream showed much higher than that of upstream because of the high ratio of agricultural area. As a result of analysis of soil loss, unit soil loss of upstream is 4.3 times than soil loss of downstream. Therefore, the establishment of countermeasures for upstream is more efficient to reduce soil loss.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.5
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• pp.1-11
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• 2015

Jeju Island is managed intensively in terms of environmental and ecological aspect because of its extraordinary ecosystem types comprising numerous rare, protected flora and fauna. To depict rapid change of habitat status in Jeju Island, the InVEST Habitat Quality model has been operated and compared analytically with the Eco-Natural map. The Habitat Quality map of Jeju Island is turned out to have similar inclination with Eco-Natural map. We compared the average habitat quality value in each Eco-natural map class in Jeju Island and the habitat quality value of first second third grade and non-included area decreased as 0.95 0.76, 0.53 and 0.37 in eco natural map respectively. Compared to biodiversity map based on biological investigation, the result of the InVEST habitat quality model can be simply obtained by land cover map with threat and sensitivity data. Further studies are needed to make explicit coefficients for Jeju Island and Korean peninsula, then the Habitat Quality model could be applied to past and future scenarios to analyze extent of habitat degradation in time series to help decision makers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.143-150
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• 2013

Recently, environmental issues such as climate warming, ozone layer depletion, reduction of tropical forests and desertification are emerging as global environmental problems beyond national problems. And international attention and effort have been carried out in many ways to solve these problems. In this study, the growth of green was calculated quantitatively using the technique of remote sensing and temperature change was figured out through temperature extraction in the city. The land-cover changes and thermal changes for research areas were analyzed using Landsat TM images on May 2002 and May 2009. Surface temperature distribution was calculated using spectral degree of brightness of Band 6 that was Landsat TM thermal infrared sensor to extract the ground surface temperature in the city. As a result of research, the area of urban green belt was increased by $2.87km^2$ and the ground surface temperature decreased by $0.6^{\circ}C{\sim}0.8^{\circ}C$ before and after tree planting projects. Henceforth, if the additional study about temperature of downtown is performed based on remote sensing and measurement data, it will contribute to solve the problems about the urban environment.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.611-619
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• 2013

Although the need of crop production has increased in Mongolia, crop cultivation is very limited because of the harsh climatic and topographic conditions. Crop lands are sparsely distributed with relatively small sizes and, therefore, it is difficult to survey the exact area of crop lands. The study aimed to find an easy and effective way of accurate classification to map crop lands in Mongolia using satellite images. To classify the crop lands over the study area in northern Mongolia, four classifications were carried out by using 1) Thematic Mapper (TM) image August 23, 2) TM image of July 6, 3) combined 12 bands of TM images of July and August, and 4) both TM images of July and August by layered classification. Wheat and potato are the major crop types and they show relatively high variation in crop conditions between July and August. On the other hands, other land cover types (forest, riparian vegetation, grassland, water and bare soil) do not show such difference between July and August. The results of four classifications clearly show that the use of multi-temporal images is essential to accurately classify the crop lands. The layered classification method, in which each class is separated by a subset of TM images, shows the highest classification accuracy (93.7%) of the crop lands. The classification accuracies are lower when we use only a single TM image of either July or August. Because of the different planting practice of potato and the growth condition of wheat, the spectral characteristics of potato and wheat cannot be fully separated from other cover types with TM image of either July or August. Further refinements on the spatial characteristics of existing crop lands may enhance the crop mapping method in Mongolia.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.129-143
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• 2014

The purpose of this study is to evaluate flooding vulnerability considering spatial characteristics focused on Changwon-si, Gyeongsangnam-do. Assessment Factors are water cycle area ratio, surface runoff, and precipitation. And construction of assessment factors and vulnerability was analyzed by GIS program. Water cycle ratio and surface runoff were vulnerable in urban area. Precipitation was often distributed in agriculture of the northern region. Results of flooding vulnerability were low in agriculture and forest of the northern region. In contrast, urban area was high because there has covered impervious land cover. Analytical results of flooding vulnerability density using hotspot spatial cluster analysis were high in urban area. And these areas were situated in down stream so flooding were generated. Therefore, flooding vulnerability assessment of this study can help for selecting construction sites of pervious land cover and rainwater management facilities in urban and environmental planning.

• Economic and Environmental Geology
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• v.37 no.5
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• pp.521-532
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• 2004

The aim of this study is to evaluate the susceptibility of landslides at Kangneung area, Korea, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified from interpretation of satellite image and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS and remote sensing data. Using frequency ratio model which is one of the probability model, the relationships between landslides and related factors such as slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil, type, age, diameter and density of wood, lithology, distance from lineament and land cover were calculated as frequency ratios. Then, the frequency ratio were summed to calculate a landslide susceptibility indexes and the landslide susceptibility maps were generated using the indexes. The results of the analysis were verified and cross-validated using actual landslide location data. The verification results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.1
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• pp.57-78
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• 2017

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.