기후 변동성과 시장 불확실성이 심화되는 상황에서 노지 작 물의 작황 모니터링은 점차 중요성이 커지고 있다. 기상자료 통계분석, 원격탐사기반 식생지수, 작물모형 중 하나에만 의 존하는 기존 모니터링 접근법은 부분적인 정보만 제공할 뿐, 현장상황을 종합적으로 판단하여 제시하지 못하는 한계가 있 다. 본 연구는 다중출처 데이터와 작물모형을 통합하여 지역 단위 작황 모니터링을 자동으로 수행하는 보고 서비스 개발을 목표로 한다. 제안하는 서비스는 (1) 기상자료 분석을 통한 환 경 특성 평가, (2) 위성영상을 활용한 식생지수 산출을 통한 실 시간 생육 상태 진단, (3) 작물모형을 활용한 기상환경에 따른 잠재 생산량 추정의 세 요소로 구성된다. 이러한 데이터는 파 이프라인을 통해 자동으로 처리하여 그 결과가 지도, 시계열 변화, 생산량 예측을 포함한 지역 단위 작황 보고서로 생성되 도록 시스템을 개발하였다. 잠재생산량은 생산량 통계 자료 와의 비교 검증을 통해 작물모형(APSIM)을 활용한 잠재 생 산량 추정치가 유의한 수준임을 확인하였다. 본 연구에서 제 안한 체계는 다양한 출처에서 생산되는 데이터를 자동화된 보 고 파이프라인으로 통합함으로써 농업 의사결정, 정책 수립, 기후 및 시장 위험에 대한 신속한 대응을 지원할 수 있는 의사 지원시스템의 주요 구성요소로 기여할 것이다.

Welding is one of representative manufacturing processes in the industrial field. Cryogenic storage containers are also manufactured through welding, and conversion to laser welding is issue in the field due to many advantages. Since welding causes thermal-elastic deformation, design considering distortion is required. Prediction of distortion through FEM is essential, but laser welding has difficulties in the field because there is no representative heat source model. The author presented the model that can cover various models using a multi-layer heat source model in previous studies. However the previous study has a limitation which is a welding heat source model must be derived after performing bead on plate welding. Thus this study was attempted to estimate the welding heat source parameters by comparing the shape of bead under various conditions. First, the difference between penetration shape and welding heat source parameters according to welding power was analyzed. The radius of the welding heat source increased according to the welding power, and the depth of the welding heat source also increased. The correlation between the penetration shape and the welding heat source parameter appears at a similar rate, however the follow-up research is necessary with more model data.

Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.

Recently, spatial data integration for geoscientific application has been regarded as an important task of various geoscientific applications of GIS. Although much research has been reported in the literature, quantitative assessment of the spatial interrelationship between input data layers and an integrated layer has not been considered fully and is in the development stage. Regarding this matter, we propose here, methodologies that account for the spatial interrelationship and spatial patterns in the spatial integration task, namely a multi-buffer zone analysis and a statistical analysis based on a contingency table. The main part of our work, the multi-buffer zone analysis, was addressed and applied to reveal the spatial pattern around geological source primitives and statistical analysis was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multi-source geoscience data sets from Ogdong in Korea was applied to illustrate application of this methodology.