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Optimal Spatial Interpolation Method Considering Topography and Density of Geotechnical Information : 지반정보의 밀도와 지형을 고려한 최적 공간보간 방법
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 정충기 | - |
dc.contributor.author | 정택규 | - |
dc.date.accessioned | 2018-12-03T01:48:47Z | - |
dc.date.available | 2018-12-03T01:48:47Z | - |
dc.date.issued | 2018-08 | - |
dc.identifier.other | 000000152574 | - |
dc.identifier.uri | https://hdl.handle.net/10371/144019 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 공과대학 건설환경공학부, 2018. 8. 정충기. | - |
dc.description.abstract | Kriging is widely used in many fields to interpolate spatial data. Kriging is a geo-statistical method that predicts property values at unknown points using a weighted linear combination through known values of given points. Since geotechnical information can be irregularly distributed in the target area due to topographic and artificial factors, it is more efficient to apply spatial interpolation in the target area. However, when kriging is generally applied, there is a problem that the influence of the topographic classification and the topography characteristics is not considered. Therefore, it should consider the topographic classification, density of geotechnical investigation data, and grid size for dividing the area to perform reliable spatial interpolation.
The aim of this research is to propose a reasonable spatial interpolation method with high reliability when considering the effects of topographical characteristics (average slope, adjacent slope), grid size and density of borehole data. The geotechnical investigation data input form was standardized by DB schema. And the elevation of borehole data was corrected through the design guideline. To perform the topographic classification, the slope of the DEM was calculated by neighborhood algorithm, which is generally used to analyze slope. The target area was divided into 0.25km × 0.25km, 0.5km × 0.5km, and 1km × 1km, and spatial interpolation was performed by average ground condition (0.25km × 0.25km) and simple kriging for each layer boundary elevation and thickness. The optimal spatial interpolation method was proposed by using kriging and average ground condition. | - |
dc.description.tableofcontents | Chapter 1 Introduction 1
1.1 Background 1 1.2 Objectives 4 1.3 Disseration Organization 4 Chapter 2 Literature Review 5 2.1 Geotechnical Information System 5 2.1.1 Geographic Information System 5 2.1.2 Database Management System 6 2.2 General Feature of Topography 8 2.3 Geo-statistical Interpolation 11 Chapter 3 Standardization of Borehole Dataset 15 3.1 Standardization of Borehole Data 15 3.2 Development Database and Database Schema 16 3.3 Accuracy Evaluation of Borehole Data 18 Chapter 4 Topographic Classification 21 4.1 Slope Analysis Algorithm 21 4.2 Method of Topographic Classification 26 4.3 Distribution of Topography 29 Chapter 5 Optimal Spatial Interpolation Method 31 5.1 Method of Spatial Interpolation Analysis 31 5.2 Outlier Analysis 36 5.3 Application of the Proposed Method 39 Chapter 6 Conclusions 49 References 51 | - |
dc.format | application/pdf | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject.ddc | 624 | - |
dc.title | Optimal Spatial Interpolation Method Considering Topography and Density of Geotechnical Information | - |
dc.title.alternative | 지반정보의 밀도와 지형을 고려한 최적 공간보간 방법 | - |
dc.type | Thesis | - |
dc.description.degree | Master | - |
dc.contributor.affiliation | 공과대학 건설환경공학부 | - |
dc.date.awarded | 2018-08 | - |
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