Interpolation and visualization of sparse GPR data

Sammanfattning: Ground Penetrating Radar is a tool for mapping the subsurface in a noninvasive way. The radar instrument transmits electromagnetic waves and records the resulting scattered field. Unfortunately, the data from a survey can be hard to interpret, and this holds extra true for non-experts in the field. The data are also usually in 2.5D, or pseudo 3D, meaning that the vast majority of the scanned volume is missing data. Interpolation algorithms can, however, approximate the missing data, and the result can be visualized in an application and in this way ease the interpretation. This report has focused on comparing different interpolation algorithms, with extra focus on behaviour when the data get sparse. The compared methods were: Linear, inverse distance weighting, ordinary kriging, thin plate splines and fk domain zone-pass POCS. They were all found to have some strengths and weaknesses in different aspects, although ordinary kriging was found to be the most accurate and created the least artefacts. Inverse distance weighting performed surprisingly well considering its simplicity and low computational cost. A web-based, easy-to-use visualization application was developed in order to view the results from the interpolations. Some of the tools implemented include time slice, crop of a 3D cube, and iso surface.