• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.36-46
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• 2007

The primary purpose of this study is to identify the characteristics of land use change at the urban fringe. For this purpose, the Daegu Metropolitan City is selected as a study area. Land use changes between 1990 and 2000 in fringe areas are identified by processing Landsat TM5 imageries. The main findings are follows: First, land development has been driven by residential development, especially large-scale residential development encouraged by the two-million housing construction plan. Second, the type and size of the land use conversion are not identical across the study area. For example, the main land use type of the newly developed area of Buk-gu is residential use while that of Suseong-gu is public use. Third, most of residential development type is a high-density development which is quite different from American type of low-density development.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.354-359
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• 2009

Land cover types of Hustai National Park (HNP) in Mongolia, a hotspot area with rare species, were classified and their temporal changes were evaluated using Landsat MSS TM/ETM data between 1994 and 2000. Maximum likelihood classification analysis showed an overall accuracy of 88.0% and 85.0% for the 1994 and 2000 images, respectively. Kappa coefficients associated with the classification were resulted to 0.85 for 1994 and 0.82 for 2000 image. Land cover types revealed significant temporal changes in the classification maps between 1994 and 2000. The area has increased considerably by $166.5km^2$ for mountain steppe. By contrast, agricultural areas and degraded areas affected by human being activity were decreased by $46.1km^2$ and $194.8km^2$ over the six year span, respectively. These areas were replaced by mountain steppe area. Specifically, forest area was noticeably fragmented, accompanied by the decrease of $\sim400$ ha. The forest area revealed a pattern with systematic gain and loss associated with the specific phenomenon called as forest free-south slope. We discussed the potential environmental conditions responsible for the systematic pattern and addressed other biological impacts by outbreaks of forest pests and ungulates.

• Forest Science and Technology
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• v.14 no.4
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• pp.181-191
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• 2018

This study was carried out in the teaching and research forest of the University of Dschang in Belabo, with the aim of analysing land-cover and land-use changes as well as carbon stocks dynamic. The databases used are composed of three Landsat satellite images (5TM of 1984, 7ETM + of 2000 and 8OLI of 2016), enhanced by field missions. Satellite images were processed using ENVI and ArcGIS software. Interview, focus group discussion methods and participatory mapping were used to identify the activities carried out by the local population. An inventory design consisting of four transects was used to measure dendrometric parameters and to identify land-use types. An estimation of carbon stocks in aboveground and underground woody biomass was made using allometric models based on non-destructive method. Dynamic of land-cover showed that the average annual rate of deforestation is 0.48%. The main activities at the base of this change are agriculture, house built-up and logging. Seven types of land-use were identified; adult secondary forests (64.10%), young secondary forests (7.54%), wetlands (7.39%), fallows (3.63%), savannahs (9.59%), cocoa farms (4.28%) and mixed crop farms (3.47%). Adult secondary forests had the highest amount of carbon ($250.75\;t\;C\;ha^{-1}$). This value has decreased by more than 60% for mixed crop farms ($94.67\;t\;C\;ha^{-1}$), showing the impact of agricultural activities on both forest cover and carbon stocks. Agroforestry systems that allow conservation and introduction of woody species should be encouraged as part of a participatory management strategy of this forest.

• Korean Journal of Environment and Ecology
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• v.19 no.4
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• pp.375-384
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• 2005

This study was conducted selecting 44 places with a block unit subject to urban area in Gangnam-gu, to analyze a temperature change according to land use and green structure. In this study, it was used the broad-wide urban temperature, supported by Landset TM and ETM+ satellite image 6scene(1999${\~}$2002). The result of the research, the land use pattern has slightly influence on a temperature change of urban area. The result from correlation analysis between temperature and the factors affected by land cover type, such as building-to-land ratio(A correlation coefficient is 0.368${\~}$0.709) have positive correlation and green area ratio(a correlation coefficient is -0.551${\~}$-0.860) have negative correlation. The result from correlation analysis between temperature and green capacity of the land, crown projection area ratio, each factor have negative correlation with temperature, as showing that a correlation coefficient of green capacity of the land is -0.577(June 2006)${\~}$-0.882(June 1999) and crown projection area ratio's is -0.549(June 2001)${\~}$-0.817(June 1999). The result of the regression analysis for establishing urban area temperature change prediction model showed that green capacity of the land of the explanation variable was accepted.

• Journal of the Korean Geographical Society
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• v.35 no.1
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• pp.3-15
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• 2000

산업화와 더불어 심각해지고 있는 수질오염 문제를 해결하기 위해서는 여러 가지 수질관리 방안이 요구된다. 수질오염이 과거에는 국지적이었으나 점차 광범한 지역으로 확장됨에 다라 지속적인 수질 모니터링에 어려움이 따른다. 본 연구에서는 위성영상을 사용한 원격탐사 기법으로 수역의 수질환경 인자를 추출하고자 한다. 사용된 영상은 Landasat TM이며, 연구지역은 한강하류 지역이다. 수질분석 인자는 클로로필-a, 부유물질, 투명도 등을 선정하였으며, 수면분광반사율의 특징 및 수질인자별 처리기법을 개발하는데 목적을 두었다. 분광특성 분석결과를 요약하면, 첫 번째 스펙트럼 반사율 분석결과 클로로필-a의 농도는 0.4~0.5$\mu\textrm{m}$ 파장대역에서 낮은 반사치 경향을 보이며, 녹색파장대인 0.57$\mu\textrm{m}$ 부근에서 반사율이 높아진다. 두 번째 부유물질의 반사도는 농도가 증가할수록 0.8$\mu\textrm{m}$ 부근에서 상대적으로 낮은 반사율이 나타난다. 마지막으로 투명도가 낮은 수면은 0.55$\mu\textrm{m}$에서 높은 반사율 경향을 보인다. Landsat TM영상을 이용하여 주성분분석 및 비연산처리를 실시하여 수질분석을 시도한 결과를 보면 클로로필-a와 투명도는 제1주성분 영상 및 제2주성분 영상에서 현장 실측자료와 유사한 결과를 얻을 수 있었으며, 부유물질은 밴드 2와 밴드 4의 비연산처리를 통하여 분포도를 작성할 수 있었다. 이상의 결과들은 계절적 및 시간적 변화에 따라 파장대역이 달라질 수 있다. 그러므로 위성자료를 이용하여 보다 정확한 수질환경 인자를 추출하기 위해서는 현장실측 및 수역의 분광반사 특성을 지속적으로 조사하여야 한다.때문으로 경주 산사태와 포함-구릉포간 국도면의 산사태가 이 종류의 산사태에 속한다.열 인식의 신뢰도를 향상시킬수 있는 방법을 제안하였다.작성하여 최신 의료영상 처리 기법을 쉽게 임상에 적용하고 실험할 수 있는 장점이 있다. 지대에서 가능하였고, 파종기는 중생종보다 이르게 나타났다. 등숙만한출수기 기준의 안전작기는 조생종과 중생종은 태백고냉지대와 태백준고냉지대, 소백산간지대 일부지역을 제외한 다른 지역에서 설정되었고, 중만생종은 태백고냉지대, 태백준고냉지대, 동해안북부지대, 소백산간지대, 노령소백산간지대의 일부 지역은 벼 담수직파가 불가능하게 판단되었다. information on the regular basis of time and provide it when the users query over the Web-database gateway. The other approach is a shopping agent mechanism, which stores information on "how to shop" and the shopping agent collects the information of product items just after users query about the product and provide the information in real time or notify them by alerting service. Thirty nine shopping information services are compared and classified in this paper and they are extracted from "Naver" and "Yahoo! Korea". The final result shows that most services are just a

• 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.

• 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.

• 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.101 no.3
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• pp.374-380
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• 2012

The k-Nearest Neighbor (kNN) technique is popularly applied to assess forest resources at the county level and to provide its spatial information by combining large area forest inventory data and remote sensing data. In this study, two approaches such as distance-weighting and stratification of training dataset, were compared to improve kNN-based forest growing stock estimates. When compared with five distance weights (0 to 2 by 0.5), the accuracy of kNN-based estimates was very similar ranged ${\pm}0.6m^3/ha$ in mean deviation. The training dataset were stratified by horizontal reference area (HRA) and forest cover type, which were applied by separately and combined. Even though the accuracy of estimates by combining forest cover type and HRA- 100 km was slightly improved, that by forest cover type was more efficient with sufficient number of training data. The mean of forest growing stock based kNN with HRA-100 and stratification by forest cover type when k=7 were somewhat underestimated ($5m^3/ha$) compared to statistical yearbook of forestry at 2011.