## 5 Conclusions  
A preprocessing phase for optimum site classification was proposed with a sophisticated computerized framework based on geoinformatics. For reliable geospatial assessment, a geotechnical  
Figure 11: Maps showing the results of using principal component analyses to unify the multilayer seismic zonation for the parameter combinations shown in Table 3: (**a**) combination #1; (**b**) combination #2; and (**c**) combination #3. (**d**) Map showing the seismic zonation with administrative sub-units generated using the average principal component-based site class (Table 1) and combination #3 for each clustered mesh. DB for Daejeon city was optimized by screening the incorrect properties using a quality assurance technique and a hybrid model of outlier detection. The DB was clustered about the geo-layer thickness and average \(N_{60}^{exp}\), using hot spot analysis methods that included estimates of the KDE, local Moran's I, and Getis-Ord Gi*. Consequently, a zonal geotechnical characteristic was developed as a multiscale geometry using the optimum geospatial prediction with high accuracy by comparing the prediction residuals from their cost functions by cross-validation. Finally, a seismic zonation was generated according to the multivariate site classification system. To support the conservative seismic decision-making process, vulnerable zones based on \(V_{530}\) were concentrated in the central urban area. The PCA of the multilayered zonation provided a unified zonation map that considered the priorities of multiscale grid-based \(V_{530}\), \(H\), and \(T_{G}\). Based on multiple geospatial datasets from Daejeon city, a multilayer geospatial information system with spatial bias and different resolutions was used to construct an integrated geospatial DB. The DB contained data regarding the surficial and subsurface composition of the area to assess the regional seismic site effect. In the in situ geotechnical DB, outliers were mostly detected in linear clusters along roads and railroads, due to the high negative local values over approximately 10% of the cross-validation residuals. Hot spots (high kernel density and strong positive value clusters) of the geotechnical attributes were assembled and reviewed to sub-group the multiscale grid. The grid was generated using geospatial interpolation methods (IDW or SK) with high prediction accuracy and a high correlation between the geo-layer structure and stiffness. In particular, the PCA-based unification of the site classification map was effective for representation of the central old urban region of the city, showed a deviation in seismic site effects. Thus, a phased spatial solution to characterize spatial uncertainties in geotechnical attributes and associated mapping of seismic zonation produced higher resolution and more reliable results than conventional zonation. The integration of remote sensing-based and in situ geotechnical information is essential considering spatial correlations and bias, to build digital soil maps and seismic zonation in thematic application such earthquake hazard assessment. Specifically, borehole datasets providing only one-dimensional profile having the stochastic and spatial uncertainty should be proved based on the quality assurance. The spatially not coincided and corresponding geotechnical properties were mostly distributed in mountain and shallow soft deposit. The multi-scale clustering for geospatial interpolation is also more effective in urban area with dense and low variable soil information. Thus, for application of the proposed geospatial characterization procedures in other or global site, the collection of reliable soil investigation and monitoring based large-scale data should be preceded. For featured application, this framework and seismic zonation mapping can be developed as the decision support system for regional earthquake hazard assessment. It is also possible engineering approach in the field of site-specific seismic design and performance evaluation in urban areas considering geospatial uncertainties.