Abstract
Seismic site effects are influenced mainly by geospatial uncertainties corresponding to geological or geotechnical spatial variance. Therefore, the development of a geospatial database is essential to characterize site-specific geotechnical information in multiscale areas and to optimize geospatial zonation methods with potentially high degrees of spatial variability based on trial-and-error geostatistical assessments. In this study, a multi-source geospatial information framework, which included the construction of a big data platform, estimation of geostatistical density, optimization of the geostatistical interpolation method, assessment of seismic site effects, and determination of geospatial zonation for decision making, was established. Then, this framework was applied to the Seoul metropolitan area, South Korea. The GIS-based framework was established to develop the geospatial zonation of site-specific seismic site effects before considering the local characteristics of site effects dependent on topographic or geological conditions, based on a geospatial big-data platform in Seoul. The zonal conditions were composed of geo-layers, site effect parameters, and other multi-source geospatial maps for each administrative area, and infrastructure was determined based on the integration of the optimized geoprocessing framework.
Highlights
The development of geospatial databases is essential for the characterization of local geotechnical information in multiscale areas using optimized geotechnical survey results that have potentially high degrees of spatial variability based on geostatistical assessments
Seismic zonation in the Seoul metropolitan area was determined using multiple geo-datasets according to the framework proposed
Geospatial zonation of seismic site effects was applied and validated in Seoul, South Korea, based on a big data platform, which was integrated with multi-source geo-layer information
Summary
The development of geospatial databases is essential for the characterization of local geotechnical information in multiscale areas using optimized geotechnical survey results that have potentially high degrees of spatial variability based on geostatistical assessments. Geospatial information has been applied recently as a big data platform to construct potential earthquake hazard maps that consider site effects. Based on the big data platform, site classification can be performed with regard to infrastructure, administrative boundaries, and other surface information that corresponds to spatial uncertainties by confining the appropriate geostatistical models for each specific area with similar characteristics using site effect parameters derived from geotechnical datasets. A multi-source geospatial information framework, which included the construction of a big data platform, estimation of geostatistical density, optimization of the geostatistical interpolation method, assessment of seismic site effects, and determination of geospatial zonation for decision making, was created and applied to the Seoul metropolitan area in South Korea
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
