• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2003년도 총회 및 춘계학술발표회
• /
• pp.97-99
• /
• 2003

Lineament density maps can be used for the quantitative evaluation of relationship between lineaments and groundwater occurrence. There are several kinds of lineament density maps including lineament length density, lineament cross-points density, and lineament counts density maps. This paper reports the usefulness of the representative elementary area (REA) concept for lineament analysis. This concept refers to the area size of the unit circle to calculate the lineament density factors distributed within the circle: length, counts and cross-points counts. The circle is a unit circle that calculates the sum of the lineament length, lineament counts and the number of cross-points within it. The REA is needed to obtain the best representative lineament density map prior to the analysis of relation between lineaments and groundwater well yield or other groundwater characteristics. A basic lineament map for the Yongsangang-Seomjingang watershed of Korea, drawn from aerial black-and-white photographs of 1/20, 000 scale was used for demonstrating the concept. From this study, the conclusions were as follows: (1) the REA concept can be efficiently applied to the lineament density analysis and mapping, (2) for whole Yongsangang-Seomjingang watershed which has 6, 502 lineaments with an average lineament length of 3.3 km, the lower limits of each REA used for drawing the three density maps were about 1.77 $\textrm{km}^2$ (r=750 m) for lineament length density, 7.07 $\textrm{km}^2$ (r=1, 500 m) for lineament counts density, and 4.91 $\textrm{km}^2$ (r=1, 250 m) for lineament cross-points density, respectively, (3) the lineament densities are inversely proportional to the size of REA, and the REA can be calculated with this inversely linear regression model, (4) if the average lineament density values for the whole study area are known, the most accurate density maps can be drawn using the REAs obtained from each linear regression model, and (5) but critical attention should be paid to draw lineament counts density and lineament cross-points density maps because.

• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2005년도 총회 및 춘계학술발표회
• /
• pp.85-89
• /
• 2005

Lineament maps are the important tools that may reveal points of groundwater recharge, flow and development. In particular, groundwater flows and yields in mountainous area, composed of crystalline rocks with many fractures, are governed mainly by the lineaments corresponding to fractures, joints and faults. Lineaments may give important information on the best distribution of wells and their management. For two districts; Pohang and Cheonan, the relationship between lineament and groundwater factors was analyzed. To compare groundwater productivity, storativity, and transmissivity of a well site along the distance to lineament, the distances to lineament was regrouped into five groups with an equal range, 100m, for the Pohang district and they are also divided into five groups with an equal range, 150m, for the Cheonan district. From the results of the Spearman Rank Correlation Analysis and Kendall Analysis for each group, the means of SPC and T of wells which are located near lineaments generally have large values. The means of SPC and T show a reverse linear relationship with a lineament distance, but the means of S shows a disperse distribution and no distinct linear relation. Result of the linear regression model between SPC and lineament length density shows that it will be effective to use the lineament length density map when finding the optimal well site on a regional scale.

• 대한원격탐사학회지
• /
• 제1권1호
• /
• pp.39-51
• /
• 1985

The study was emphasized on application of the digital image processing techniques for lineament analysis. The major lineament of the study area belongs to Choogaryong faults which many geologists have studied since 1903. Also the lineament is so significant in geological views, because the lineament runs through Seoul area. The several image processing methods such as gradient, Laplacian and spatial filter have been applied, and the spatial filtering is most suitable method for lineament analysis among them. The lineaments distribute predominently in the N20.deg.-30.deg.E trend and N80.deg.-90.deg.W trend which have the conjugated relationship each other, and it coincides with the Gyeongsang conjugate system. The circular structure of study area was developed by cooling circular joint.

• International Journal of Advanced Culture Technology
• /
• 제10권2호
• /
• pp.187-193
• /
• 2022

We is configured the honk changing-status technique that is to meld the square-built blow-shock status of the gleam-differential perception level (BIAL) on the honk perception lineament. The perception level condition by the honk perception lineament system is constituted with the blow-shock system. As to experimentation a ductile-dot of the gleam ductile-dot, we are found of the honk value with ductile-dot by the blow upper shift. The concept of perception level is constituted the reference of gleam-differential level for changing-status signal by the honk shock lineament. Further symbolizing a square-built changing-status of the BIAL, of the average in terms of the blow-shock lineament, and the honk ductile-dot shock that was the honk value of the far changing-status of the Ho-PL-FA-θ_AVG with 15.41±8.63 units, that was the honk value of the convenient changing-status of the Ho-PL-CO-θ_AVG with 8.70±3.06 units, that was the honk value of the flank changing-status of the Ho-PL-HO-θ_AVG with 2.65±1.19 units, that was the honk value of the edge changing-status of the Ho-PL-VI-θ_AVG with 0.51±0.18 units. The blow shock will be to investigate at the square-built ability of the blow-shock lineament with ductile-dot by the honk perception level on the BIAL, that is denote the gleam-differential lineament by the perception level system. We will be possible to curb of a lineament by the differential signal and to employ the honk data of blow shock level by the blow perception system.

• 대한원격탐사학회지
• /
• 제7권1호
• /
• pp.29-43
• /
• 1991

The study was performed to extraction the ground water potential area using LANDSAT TM data. The image processing techniques developed for the study are contrast transformation, differential filtering and pseudo stereoscopic image methods. These were examined for lineament extraction, lineament interpretation and the integration of vertor data with LANDSAT data. The differential filtering method is much usefull for lineament extraction, and all direction lineaments are clearly shown on the band 5 image of LANDSAT TM. The pseudo stereoscopic image are made in which color differential method is adopted, the pair images are usefull for the lineament interpretation. The results of the analysis are as follows. 1) there is a close correlation between lineament and cased well in the study area, because 33 wells of the developed 45 cased wells coincide with the lineaments. 2) 21 sites in the study area were selected for pumping test, and as a result 11 sites of them produces over than 200 ton/day.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.411-420
• /
• 1999

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

• 한국지형학회지
• /
• 제23권2호
• /
• pp.61-70
• /
• 2016

This study intended to analyze the spatial distribution of two types of weeding song (Short Bang-a and Sangsa ryu) and how geomorphic elements influence the propagation of the songs in Chungcheongbuk-do area. The distribution of the two types of song was mapped as point data. According to the result, both types showed similar distribution pattern. In order to figure out the reason of this similarity, the distribution pattern of songs was analyzed at various scales based on geomorphic elements including river, mountain and lineament. The result showed that most of distribution pattern of songs followed the lineament direction. Also, the spatial continuity among mountain that was formed by large and small lineament in various directions could be the path of the cultural diffusion. If the lineament with same direction does not intersect other lineament that have different direction, spatial continuity would be blocked. Consequently it was confirmed that propagation of songs has not spread smoothly.

• 한국지리정보학회지
• /
• 제19권3호
• /
• pp.61-74
• /
• 2016

본 연구에서는 LANDSAT 8호, KOMPSAT 2호 위성영상과 1/25,000 수치지형도를 기반으로 작성된 음영기복도를 이용하여 2007년 1월 20일 오대산 지역에서 발생한 약 4.8의 중규모 지진과 선구조선의 관계를 분석하였다. 대부분의 선행연구는 지체구조와 관련된 선구조선 분석 연구를 하였으며, 주로 2차원의 위성영상과 음영기복도를 활용하였기에 지형의 기복 등에 대한 판독이 어려워 선구조선 추출이 제한적이었다. 본 연구에서는 이를 보완하기 위해 수치표고모델(Digital Elevation Model; DEM)을 기반으로 작성한 3차원 입체 영상과 수계망 분석을 통해 지형의 기복, 수계의 연결성 등을 판독해 선구조선을 추출하여, 2차원 영상에서 나타나는 시각적인 판독에 의한 오류를 최소화한 선구조선 판독도를 작성하였다. 또한 진앙에 대한 선구조선의 통계 요소별 밀도를 추정하기 위해 spline 내삽법을 이용하여 선구조선의 빈도, 교차점, 길이에 대한 밀도를 계산하였다. 그리고 진앙에서의 선구조선 밀도가 얼마나 밀집되어 있는지 정량적으로 표현하기 위하여 각 격자 내의 선구조선 밀도에 대해 최대 선구조선 밀도로 나누는 상대밀도 값(Value of the Relative Density; VRD)을 계산하는 알고리즘을 개발하여 밀도도(density map)를 작성하였다. 각 영상의 진앙에서의 VRD는 최소 약 0.60에서 최대 약 0.90으로 나타났지만, 각 영상별 광원의 고도각과 방위각이 차이가 있어 영상별 VRD보다 통계 요소별 VRD의 평균치를 사용하였다. 그 결과, 빈도의 평균 VRD는 약 0.85로 교차점과 길이의 평균 VRD보다 약 21% 높게 나타나, 선구조선의 빈도 요소가 진앙의 위치와의 관계가 가장 밀접함을 확인하였다. 이와 같이 3차원 영상의 선구조선 추출을 통한 밀도 분석 기술은 향후 지진 발생 가능 지역 분석에 기초자료로써의 의미가 있을 것으로 기대된다.

• 자원환경지질
• /
• 제51권2호
• /
• pp.167-176
• /
• 2018

고준위방사성폐기물 처분장 부지선정을 위해서는 암종, 지질구조, 지진, 수리지질, 지구화학, 지질공학 및 지열 등과 같은 다양한 지질학적 인자들에 대한 고려가 필요하며, 특히 선형구조는 다양한 지질인자의 특성을 반영하기 때문에 원자력 발전소, 고준위방사성폐기물 처분장 등과 같은 국가 중요시설물의 후보부지 선정에 있어 매우 중요한 기초자료로 활용될 수 있다. 본 논문에서는 선형구조분석을 통해 고준위방사성폐기물 광역 처분부지 선정을 실시한 핀란드의 선형구조 분류 방법을 국내 선형구조 자료에 적용하여 살펴보았다. 이를 위하여 기존에 한국지질자원연구원에서 보유한 선형구조도와 신규로 구조지질학, 고지진학, 지형학 전문가들로부터 획득한 새로운 선형구조 자료를 분석에 이용하였다. 새로운 선형구조 분석 자료의 신뢰성 확보를 위해 한반도 지역을 최근에 촬영한 위성영상과 국토지리정보원에서 제공하는 수치표고모델로 제작한 고해상도의 음영기복도를 이용하였다. 취득한 자료들의 전체적인 방향성 분석 결과에서는 북북동-남남서 방향이 가장 우세하게 관찰되었지만, 분석자들의 판독기준의 차이에 따라서 동북동-서남서 및 북북서-남남동 방향의 선형구조들도 높게 판독 되었다. 핀란드의 분류 방법을 적용하여, 광역후보부지 선정에 사용되는 등급 1과 등급 2에 해당되는 선형구조들의 기하학적인 발달특성을 상호 비교해 보았다. 그 결과에서는 전체적으로 등급 1의 경우에는 공통적으로 북북동-남남서 방향이 가장 우세하였으며, 서북서-동남동 방향의 선형구조도 빈도가 높게 나타났다. 등급 2의 경우에도 북북동-남남서 방향의 선형구조가 가장 우세하게 발달하고 있으며, 분석자에 따라 서북서-동남동 또는 동북동-서남서 방향의 선형구조도 빈도가 높게 나타났다. 같은 자료를 바탕으로 실시한 선형구조분석에서도 상이한 판독 결과를 보이는 것은 판독자의 주관적인 경험 및 기준이 작용하였기 때문으로 여겨진다. 따라서 신뢰도 높은 한반도 광역선형구조도를 발간하기 위해서는 상이한 자료들을 통합하는 과정에서 명확한 통합 기준의 설정이 필요하며, 지구물리탐사자료와 같은 추가적인 데이터를 통한 분석이 요구된다.

• 한국지하수토양환경학회:학술대회논문집
• /
• 한국지하수토양환경학회 2005년도 총회 및 춘계학술발표회
• /
• pp.385-388
• /
• 2005

Through the regional lineament analysis in Korea peninsula, the statistical distribution of regional lineament is investigated. We also analyze the lineaments pattern using the fractal dimension. These results are the preliminary study for a understanding of the deep ground geological structure in Korea. For the investigations of the average block scale, we use the Dershowitz and Herda(1992)'s method. At result, the average spacing between the regional lineaments is about 10km.