• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.91-105
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• 1999

Spatial data integration using multiple geo-based data sets has been regarded as one of the primary GIS application issues. As for this issue, several integration schemes have been developed as the perspectives of mathematical geology or geo-mathematics. However, research-based approaches for statistical/quantitative assessments between integrated layer and input layers are not fully considered yet. Related to this niche point, in this study, spatial data integration using multiple geoscientific data sets by known integration algorithms was primarily performed. For spatial integration by using raster-based GIS functionality, geological, geochemical, geophysical data sets, DEM-driven data sets and remotely sensed imagery data sets from the Ogdong area were utilized for geological thematic mapping related by mineral potential mapping. In addition, statistical/quantitative information extraction with respective to relationships among used data sets and/or between each data set and integrated layer was carried out, with the scope of multiple data fusion and schematic statistical assessment methodology. As for the spatial integration scheme, certainty factor (CF) estimation and principal component analysis (PCA) were applied. However, this study was not aimed at direct comparison of both methodologies; whereas, for the statistical/quantitative assessment between integrated layer and input layers, some statistical methodologies based on contingency table were focused. Especially, for the bias reduction, jackknife technique was also applied in PCA-based spatial integration. Through the statistic analyses with respect to the integration information in this case study, new information for relationships of integrated layer and input layers was extracted. In addition, influence effects of input data sets with respect to integrated layer were assessed. This kind of approach provides a decision-making information in the viewpoint of GIS and is also exploratory data analysis in conjunction with GIS and geoscientific application, especially handing spatial integration or data fusion with complex variable data sets.

• Journal of Families and Better Life
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• v.31 no.5
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• pp.19-32
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• 2013

The purpose of this study was to identify the influences of psychological independence(functional independence and emotional independence) and career decision-making self-efficacy(self-estimation, career goal, occupational-knowledge, and problem solving) on career maturity(preparation, objective, decisiveness, and certainty) among adolescents. The subjects were 447 students in the second grade of middle school and high school in D. The questionnaire consist of measures of psychological independence, career decision-making self-efficacy, and career maturity. The data were analysed with factor analysis, Cronbach's ${\alpha}$, t-test, ANOVA, correlation and multiple regression by using the SPSS(SPSS/WIN 19.0) program. The major results were as follows. First, adolescents' the career maturity was significantly different depending on the socio-demographic variables. Second, it was shown that middle and high school students have a statically relation, in a relation among psychological independence, career decision-making self-efficacy, and career maturity. Third, it was found that psychological independence and career decision-making self-efficacy gave statistically meaningful influence on the career maturity of adolescents. This study is significant in that it suggests a plan for improving career maturity, and provides a basic material to improve one's active role in their parents. In addition, the results of this study can be used as a fundamental reference in career development programs and career-counseling centers at schools for enhancing adolescents' career development and success.