• 한국습지학회지
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• 제7권2호
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• pp.121-132
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• 2005

천수만 황도 갯벌의 IKONOS 영상을 이용한 표층 퇴적상 분류를 위하여 광학 반사도를 입도, 조류로의 형태, 지잔존수 (surface remnant water)의 면적비와 같은 다양한 퇴적환경 요소들과 비교하였다. IKONOS 영상과 갯벌 내의 소지형별 퇴적환경 사이의 관계를 분석하기 위하여 Echo-sounder를 이용하여 갯벌 Digital Elevation Model (DEM)을 만들었다. 펄-혼합 퇴적상과 모래 퇴적상의 경계에서 광학 반사도의 차이가 뚜렷하게 나타났으며 사주의 구분도 가능하였다. 펄-혼합 퇴적상 지역은 조류로가 매우 복잡하게 발달하고 있으며 지형이 상대적으로 높은 곳에 위치하고 있었다. 펄과 혼합 퇴적의 경계에서 지표수의 존재 유무가 다르게 나타났으나 광학 반사도의 차이가 뚜렷하지 않았다. 모래 퇴적상의 경우 조류로가 단순하게 직선형으로 발달했으며 지형도 상대적으로 낮은 지역에 분포하였으며 지표잔존수가 거의 전 지역을 덮고 있어 광학 반사도가 낮게 나타났다. 최대우도 분류법을 이용한 표층 퇴적상 분류정밀도는 86.2 %로 나타났다. 이 결과로부터 IKONOS와 같은 고해상도 영상에 대해 지표잔존수, 조류로 분포와 지형 등의 갯벌 퇴적학적 특성을 고려한다면 펄, 혼합 그리고 모래 퇴적상 구분은 가능하다는 것을 알 수 있다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.483-484
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• 2006

This paper introduces an improved surface matching algorithm that can be used to reconstruct the surface topography of an object that is scanned from multiple overlapping regions by an AFM. The essence of the image matching technique is stitching two neighboring images intentionally overlapped with each other. To enhance the computational efficiency, this paper introduces a pyramid matching algorithm which makes use of reduced images for primary images. The results show that the proposed image pyramid matching algorithm is useful fer enhancing the computational efficiency.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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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.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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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.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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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.

• 한국해안해양공학회지
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• 제18권1호
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• pp.63-68
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• 2006

조석 주기 동안에 시간에 따라 위치가 변하는 수륙 경계선은 조간대 지형을 측정하는 보조 자료로 활용될 수 있다. 즉 밀물 시 연속적으로 촬영된 영상으로부터 추출된 수륙경계선의 표고는 해수면 변화 자료를 이용하여 등심선으로 이용할 수 있으며 등심선의 수평거리는 영상 기하보정 처리를 통하여 정량적인 값으로 변환할 수 있다. 이러한 관측 기술을 서해안의 대이작도 큰풀안 백사장에 적용하였다. 조간대에서의 자연적인 수위변화를 이용하는 영상 관측 기법은 정확도가 높으며 또한 시간과 경제적인 측면에서 유리하다. 이러한 기술은 3차원 수조에서 연안지형 변화를 연구하는 물리모형 실험에서 시간별 지형 변화를 관측하는데 효과적으로 사용될 수 있다.

• 대한공간정보학회지
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• 제19권4호
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• pp.101-108
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• 2011

우리나라에서 남극에 장보고기지를 건설하는 계획을 추진하고 있으며 이를 위해 기지 부근 지형에 대한 상세한 정보가 필요하다. 본 연구에서는 위성영상을 이용하여 장보고기지 건설을 위한 지형도를 제작하는 것을 목적으로 연구를 수행하였다. 이를 위해 장보고기지 주변의 현지측량 및 장비의 사전테스트를 수행하였다. 또한 GeoEye-1 위성영상의 센서모델링을 위해 RPC-편의 보정을 수행하였으며 최소 두 점의 기준점이 실질적으로 필요한 것으로 나타났다. 지형도 제작은 영상의 해상도와 현지 보완측량이 불가능한 점을 고려하여 약 1/2,500의 도화축척이 적합하였다. 장보고기지 주변의 상세한 지형정보 제공을 위하여 영상정합에 의하여 수치표고모델을 생성하였으며 현지측량한 GPS-RTK 자료와 비교하였으며 약 0.6m의 수직위치정확도를 나타내었다.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2002년도 proceedings of the second asia international conference on tribology
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• pp.251-252
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• 2002

An algorithm has been developed to determine changes in surface topography on asperity level. The software stitches small but detailed images together to create one large image. If such an image is made before and after an experiment, their difference shows a direct 3D view of the changes in micro-geometry, rather than a change in surface parameters. The algorithm is described in detail and illustrated using artificial as well as real surfaces.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.568-571
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• 2005

This paper introduces a correlation-based surface matching algorithm that can be used to reconstruct the surface topography of an object that is scanned from multiple overlapping regions by an AFM. The image matching technique is applied to two neighboring images intentionally overlapped with each other. To account for the inaccuracy of the coarse stage implemented in AFM, all the six axes including the rotational degrees of freedom are successively matched to maximize the correlation coefficient. The results show that the proposed 6-axes image matching method is useful for expanding the measurement range of AFM.