• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.3
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• pp.46-53
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• 2009

Urbanization brings several changes to the natural environment. Its consequences can have a direct effect on climatic features, as in the Urban Heat Island Effect. One factor that directly affects the urban climate is the green area. In urban areas, vegetation is suppressed in order to accommodate manmade buildings and streets. In this paper we analyze the effect of green areas on the urban temperature in Seoul. The period selected for analysis was July 30th, 2007. The ground temperature was measured using Landsat TM satellite imagery. Land cover was calculated in terms of city area, water, bare soil, wet lands, grass lands, forest, and farmland. We extracted the surface temperature using the Linear Regression Model. Then, we did a regression analysis between air temperature at the Automatic Weather Station and surface temperature. Finally, we calculated the temperature decrease area and the population benefits from the green areas. Consequently, we determined that a green area with a radius of 500m will have a temperature reduction area of $67.33km^2$, in terms of urban area. This is 11.12% of Seoul's metropolitan area and 18.09% of the Seoul urban area. We can assume that about 1,892,000 people would be affected by this green area's temperature reduction. Also, we randomly chose 50 places to analysis a cross section of temperature reduction area. Temperature differences between the boundaries of green and urban areas are an average of $0.78^{\circ}C$. The highest temperature difference is $1.7^{\circ}C$, and the lowest temperature difference is $0.3^{\circ}C$. This study has demonstrated that we can understand how green areas truly affect air temperature.

• Journal of Korean Society of Forest Science
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• v.83 no.4
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• pp.460-472
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• 1994

This study has been conducted to give some ideas for reasonable ecological management of Taejon city and its adjacent forest ecosystem against the effect of acid rain. Rain monitoring points to analyse its components represented 1 point in industrial area, 4 points in commercial area, 4 points in residential area, and 5 points in suburban area and forest survey was done in 7 forest sites adjacent to rain monitoring points. Transformed vegetation index(TVI) based on Landsat TM data was analysed for forest area. Taejon area was seriously contaminated by air pollutants and average concentration of anions in precipitation were 20.16mg/l for $SO_4{^{2-}}$, 3.65mg/l for $NO_3{^-}$, and 3.09mg/l for $Cl^-$. Anion in precipitation were $1.09mg/m^2/month$ for $SO_4{^{2-}}$, $0.23mg/m^2/month$ for $NO_3{^-}$, and $0.20mg/m^2/month$ for $Cl^-$. Cation in precipitation were $0.14mg/m^2/month$ for $Ca^{2+}$, $0.10mg/m^2/month$ for $NH_4{^+}$, $0.08mg/m^2/month$ for $Na^+$, $0.07mg/m^2/month$ for $K^+$, and $0.08mg/m^2/month$ for $Mg^{2+}$. The region with the highest concentration of $SO_4{^{2-}}$, $NO_3{^-}$, and $Cl^-$ in rain was industrial area. $SO_4{^{2-}}$, $NO_3{^-}$, and $Cl^-$ concentrations in industrial area were 43.08, 3.88, and 3.64ppm, respectively. Forest soil showed strongly acidic ranging pH4.16-4.94. Transformed vegetation index(TVI) were 3.11 in Dangsan, 4.00 in Kyechoksan, 4.13 in Bomunsan, 4.18 in Kabhasan, 3.34 in Bongsan, 4.13 in Sikchangsan, and 4.20 in Seongchisan. Dangsan forest located near in industrial area showed the lowest TVI.

• Journal of Korea Water Resources Association
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• v.39 no.5 s.166
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• pp.453-466
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• 2006

The objective of this study was to analyze the changes in the hydrological environment in Soyanggang-dam watershed due to climate change results (in yews 2050 and 2100) which were simulated using CCCma CGCM2 based on SRES A2 and B2. The SRES A2 and B2 were used to estimate NDVI values for selected land use using the relation of NDVI-Temperature using linear regression of observed data (in years 1998$\sim$2002). Land use change based on SRES A2 and B2 was estimated every 5- and 10-year period using the CA-Markov technique based on the 1985, 1990, 1995 and 2000 land cover map classified by Landsat TM satellite images. As a result, the trend in land use change in each land class was reflected. When land use changes in years 2050 and 2100 were simulated using the CA-Markov method, the forest class area declined while the urban, bareground and grassland classes increased. When simulation was done further for future scenarios, the transition change converged and no increasing trend was reflected. The impact assessment of evapotranspiration was conducted by comparing the observed data with the computed results based on three cases supposition scenarios of meteorological data (temperature, global radiation and wind speed) using the FAO Penman-Monteith method. The results showed that the runoff was reduced by about 50% compared with the present hydrologic condition when each SRES and periods were compared. If there was no land use change, the runoff would decline further to about 3$\sim$5%.

• Korean Journal of Remote Sensing
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• v.8 no.1
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• pp.27-43
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• 1992

The purpose of this study is to detect and evaluate the change of urban vegetation of Seoul during 1980s. Large areas covered with agricultural crops or forests were converted to residential and commercial areas, roads, schools, sports complexes, etc. There were also widespreas concerns on the deterioration of the quality of urban vegetation due to severe air pollution, overcrowding of nature parks, and idling of farm lands by land speculators. The image used for this study were MSS(Oct. 4, 1979) and TM(Apr. 26, 1990). The Green Vegetation Index of Kauth & Thomas(1976) was for the analysis. The GVI were resampled with 75$\times$75m grids and overlaid with the jurisdictional boundaries of 22 districts of Seoul. The results were reclassified to 6 classes, class 6 representing grids with the most vigorous vegetation or the best vegetation improvement in 1980s. The finding of this study can be summarized as follows : First, the most vigorous vigorous vegetation, in terms of GVI, of the 1979 image can be found at paddy fields located on alluvial near Han River. Broad-leaf forests located on hilly terrains have higher GVI than conifers located on the upper-parts of mountains. The average GVI of the northern part and southern part of Han River are 3.56 and 3.74, respectively. The main reason why the southern part has higher GVI is that there are more prime agricultural lands. Districts of Kangseo, Yangcheon, and Songpa have the highest percentage of grids of GVI class 6, and the percentages are 3.55 %, 3.47 %, and 2.69 %, respectively. Second, the most vigorous vegetation of the 1990 image can be found at the grass lands of the Yongsan golf club and the Sungsu horse racing track. The GVI of farm lands is lower than forest because most agricultural crops are at the early stage of growing season when the TM image was taken. The size of built-up area is much larger than of 1979. On the other hand, vegetation patches surrounded by developed area become smaller and have stronger contrast to surrounding area. The average GVI of the northern part and southern part of Han River are 3.57 and 3.51, respectively. The main reason why the southern part has lower GVI is the at more large-scale urban development projects were carried out in there during 1980s. Districts of Tobong, Nowon, and Seocho have the highest percentage of class 6, and the perecentages are 16.58 %, 10.14 %, and 8.50% respectively. Third, the change of urban vegetation in Seoul during 1980s are significant. Grids of GVI change classes 1 and 2, which represent severe vegetation loss, occupy 15.97% of Seoul. Three districts which lost the most vegetation are Yangcheon, Kangseo, and Songpa, where the percentages of GVI class 1 are 13.42%, 13.39% and 9.06%, respectively. The worst deterioration was mainly caused by residential developments. On the other hand, the vegetation of some part of Seoul improved in this period. Grids of GVI change classes 5 and 6 occupy 9.83 % of Seoul. Distircts of Jung, Yongsan, and Kangnam have the highest percentage of grids with GVI change classes 5 and 6, and their percentages are 22.31%, 19.17%, and 13.66%, respectively. The improvement of vegetation occurred in two areas. Forest vegetation is generally improving despite of concerns based on air pollution and heavy use by recreationists. Vegetation in open spaces established in riverside parks, large residential areas, and major public facilities are also improving.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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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.

• The Journal of Engineering Geology
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• v.9 no.2
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• pp.161-176
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• 1999

The objectives of this study are to analyze the changes of geo-surface topography in the Siwha embankment and the Ahsan city area by the image processing of Landsat Thematic Mapper data, and to estimate the reclaimed amount of the exposed tidal flat in the Siwha area using the GIS. False color composite, Tasseled cap, NVDI(normalized difference vegetation index), and supervised classification techniques were used to analyze the distribution of sediments and the aspect of topographical variations caused by artificial human actions. The total amount of the exposed tidal flat was estimated on the basis of the database snch as aerial photography, hydrographic chart, geological map, and scheme drawing in the Siwha area. The possible excavation regions for a seawall were predicted analyzing the supervised classification image of Landsat TM data. Tasseled cap images were used to observe the distribution of sediments. The difference of the NDVI images between spring and summer seasons indicates that deciduous and coniferous forests were distributed over the whole areas. The total fill-volume of the exposed Siwha tidal flat and the fill-volume of the construction planning seawall were calculated as $581,485,354\textrm{m}^3{\;}and{\;}3,387,360\textrm{m}^3$, respectively, from the digital terrain analysis. Daebu Island, Sunkam Island, and the part of Songsan-myeon were chosen as the cut area to make the seawall, and their cut-volumes were estimated as $5,229,576\textrm{m}^3,{\;}79,227,072\textrm{m}^3,{\;}and{\;}47,026,008\textrm{m}^3$, respectively. Therefore, the cut-volume of Daebu Island alone among three areas was sufficient to make the seawall.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.23-33
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• 2009

Satellite image is very usefully practiced to predict and analyze physical expansion and change of city. Physical expansion and change of city is closely related to the use of land, and continuous growth management focused on the use of land is essential for sustainable city growth. In this research, the change of land cover and land-use were analyzed with basic input data from 1985 to 2000 according to artificial satellite. Moreover, the land-use turnover rate was understood and expansion trend of urban sprawl in Busan metropolitan city and land-use characteristics of the expansion area. The results are, first, the area for urban region was expanded continuously but areas for agriculture area, forest area, and water area had different changes due to administrative district reform of Busan by each year. Second, the urbanization area in Busan was increased by 3.8% from $92.5km^2$ in 1985 to $167.5km^2$ in 2000. Third, the result of analysis on land-use turnover rate showed that agriculture area was turned into urbanized area the most, and forest area was followed by. Fourth, the result of analysis on database and overlay of buildings in Busan established in 2001 showed that agriculture area are had type 1 and 2 neighborhood living facilities (45.63%), apartment house in forest area (18.49%), and factory in water area (31.84%) with high ratio.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.133-145
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• 2010

This study analyzed the characteristics of sediment produce by landslide triggered by rainfall. One-dimensional unsaturated groundwater model and infinite slope stability analysis were used to estimate the behavior of soil moisture and slope stability according to rainfall, respectively. Slope stability analysis was performed considering on soil depth and characteristics of trees. As the results considering on recovery of the failed slopes, much amount of sediment was produced in 1963, 1970, and 2002. As the results of verification of simulation results using Landsat 5 TM images, we can find differences of landslide location between the results from model and satellite images. These differences can be caused by uncertainties of the rough parameters in the model. However, in the case that Obong-dam basin was divided into two subbasin, Wangsan-chun and Doma-chun basin, the results of each subbasin show errors around 20%. And only 4% of error occurred in the case of comparing landslide area on the entire Obong-dam basin. These errors seem insignificant considering on the errors which can be caused from the analyses in this study such as estimation of sediment produce, soil cover classification, and estimation of landslide area.