• Korean Journal of Environment and Ecology
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• v.13 no.2
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• pp.153-159
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• 1999

이 논문은 북한산국립공원에서 1994년부터 실시하고 있는 자연휴식년제도의 효과를 검증하고 추후 휴식년의 적용이 필요한 구간을 파악하기 위하여 인공위성 영상자료를 이용하여 휴식년 적용구간과 그 주변 등산로의 식생활력의 변화를 분석하였다. 이용된 자료는 1988년, 1992년, 1994년, 1996년 9월의 Landsat TM 영상으로, ER Mapper 및 Arc/Info GIS를 이용하여 분석하였고, 식생활력의 측정은 중합차식생지수(NDVI)에 기반한 평균비율(MR)을 이용하였다. 분석결과 휴식년 적용구간의 경우 88년 이후 감소양상을 보이던 식생활력이 휴식년제도가 실시된 94년 이후 뚜렷하게 증가하여 휴식년제도의 실시가 식생활력을 증가시키는 효과가 있었음을 보여주었다. 기타 등산로의 경우는 92년 이후 식생활력이 정체 또는 감소추세를 나타내었으며, 그 중 일부 구간은 식생활력의 저하가 특히 두드러지게 나타나 추후 휴식년제도의 적용이 필요한 구간으로 판단되었다.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.7
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• pp.15-21
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• 2004

This study is to present a standardized agricultural land use classification scheme at various spatial resolution (from 1 m to 30 m) of satellite images including Landsat TM, KOMPSAT-1 EOC, ASTER VNIR and IKONOS panchromatic (PAN) and multi-spectral (MS) images. The satellite images were interpreted especially for identifying agricultural land use, crop types, agricultural facilities and structures of 18 items. It was found that there is a threshold spatial resolution between 4 m and 6.6 m to identify the full items. Thus it is suggested that IKONOS fusion image (MS enhanced by PAN) is required to produce land use map for agricultural purpose.

• Economic and Environmental Geology
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• v.30 no.3
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• pp.241-248
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• 1997

In this study, Ichon basin is selected as study area and regional analysis of geological structure are done by using lineament analysis. The factors which affects slope stability, are chosen, and integrated to database using GIS (Geoscientific Information System). Landsat TM band 4, 5 and 7 are choosen and processed by various image enhancement technique to analyse the regional geological lineaments. Spatial distribution of lineament is analysed through lineament density map and study area can be divided the eight structural domains. Considering environmental geological characteristics of study area, rating and weighting of each factors for slope stability analysis are determined and spatial analysis of regional slope stability is examined through overlaying technique of GIS. The result of areal distribution of slope stability shows that the most unstable area is all over Mt. Buksung, Mt. Daepo, Mt. Songrim and Mt. Yankak.

• Journal of Environmental Impact Assessment
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• v.11 no.4
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• pp.239-246
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• 2002

지난 몇 십 년 동안 한국에서는 도시의 확장으로 인해 인구 밀집지역에서의 토지이용이 급속하게 변화되었으며, 그 결과 도시의 환경은 악화되었다. 도시화는 도시민에 필요한 녹지의 크기와 수를 감소시킬 뿐만 아니라, 서식처 파괴의 원인이 되며, 적절한 녹지의 배치 또는 배열이 이뤄지지 않을 경우 도시내 생태적 기능의 결핍을 초래한다. 경관변화의 증명과 분석은 토지이용변화의 환경 요소의 인과관계 파악에 중요하다. 원격탐사와 지형정보체계는 토지이용 변화의 경향과 영향을 이해할 수 있어 녹지공간변화 파악에 사용된다. 원격탐사는 동일대상지의 다른 시기에서의 영상자료를 이용해 토지이용의 경년변화를 파악하며 지형정보체계는 이를 저장, 분석에 활용되고 있다. 본 연구는 원격탐사와 지형정보체계를 이용하여, 1989년부터 1998년 동안, 대전광역시의 토지이용 변화를 파악하며 그 원인을 살펴보는데 있다.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.158-167
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• 2006

The object of this study is to detect of land-cover change in western DMZ and vicinity. This was performed as a basic study to construct a decision support system for the conservation or a sustainable development of the DMZ and Vicinity near future. DMZ is an is 4km wide and 250km long and it's one of the most highly fortified boundaries in the world and also a unique thin green line. Environmentalists want to declare the DMZ as a natural reserve and a biodiversity zone, but nowadays through the strengthening of the inter-Korean economic cooperation, some developers are trying to construct a new-town or an industrial complex inside of the DMZ. This study investigates the current environmental conditions, especially deforestation of the western DMZ adopting remote sensing and GIS techniques. The Land-covers were identified through the linear spectvral mixture analysis(LSMA) which was used to handle the spectral mixture problem of low spatial resolution imagery of Landsat TM and ETM+ imagery. To analyze quantitative and spatial change of vegetation-cover in western DMZ, GIS overlay method was used. In LSMA, to develop high-quality fraction images, three endmembers of green vegetation(GV), soil, water were driven from pure features in the imagery. Through 15 years, from 1987 to 2002, forest of western DMZ and vicinity was devastated and changed to urban, farmland or barren land. Northern part of western DMZ and vicinity was more deforested than that of southern part. ($52.37km^2$ of North Korean forest and $39.04km^2$ of South Korean were change to other land-covers.) In case of North Korean part, forest changed to barren land and farmland and in South Korean part, forest changed to farmland and urban area. Especially, In North Korean part of DMZ and vicinity, $56.15km^2$ of farmland changed to barren land through 15 years, which showed the failure of the 'Darakbat' (terrace filed) project which is one of food increase projects in North Korea.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.298-301
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• 2004

The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.64-64
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• 2003

The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.65-70
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• 2003

The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$＋/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.63-63
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• 2003

The aim of this study is to apply and verify of Bayesian probability model, the likelihood ratio and statistical model, at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the likelihood ratio coefficient were overlaid for landslide susceptibility mapping, Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.