Improved IDW Interpolation Application Using 3D Search Neighborhoods: Borehole Data-Based Seismic Liquefaction Hazard Assessment and Mapping

Traditional inverse distance weighting (IDW) interpolation is a process employed to estimate unknown values based on neighborhoods in 2D space. Proposed this study an improved IDW method that uses 3D search for effective vertically connected observation data, such as water level, depth, and altitude. Borehole data are the collected by subsurface boring activities exhibit heterogeneous spatial distribution they densely populated near civil engineering or construction sites. In addition, show different characteristics depth. The observed used core modeling fields, geology modeling, estimation of groundwater table distribution, global warming assessment, seismic liquefaction among others. Therefore, proposed assessment mapping workflow using application combining geographic information system (GIS) (ArcGIS (Esri, Redlands, CA, USA)), NURBS-based CAD (Rhino/Grasshopper (Robert McNeel & Associates, Seattle, WA, numerical analysis (MATLAB (MathWorks, Natick, MA, USA)). neighborhood was conducted B-rep-based topology analysis, done under 2.5D environment voxel layer, DEM, aerial images. experiment performed collecting Songpa-gu, Seoul, which has highest population density OECD countries. results showed between 7 105 areas with potentials according approach. Finally, users’ accessibility producing web app REST API OGC I3S Standards. Such approach can be applied effectively future, it contribute expansion GIS application.