Assessment of Material Layers in Building Walls Using GeoRadar

Ildar Gilmutdinov, Ingrid Schloegel, Alois Hinterleitner, Peter Wonka, Michael Wimmer

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Assessing the structure of a building with non-invasive methods is an important problem. One of the possible approaches is to use GeoRadar to examine wall structures by analyzing the data obtained from the scans. However, so far, the obtained data have to be assessed manually, relying on the experience of the user in interpreting GPR radargrams. We propose a data-driven approach to evaluate the material composition of a wall from its GPR radargrams. In order to generate training data, we use gprMax to model the scanning process. Using simulation data, we use a convolutional neural network to predict the thicknesses and dielectric properties of walls per layer. We evaluate the generalization abilities of the trained model on the data collected from real buildings.
Original languageEnglish (US)
Pages (from-to)5038
JournalRemote Sensing
Issue number19
StatePublished - Oct 9 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-10-24
Acknowledgements: This research was funded by the Austrian Research Promotion Agency (FFG), project no. 879401 (BIMStocks). We also acknowledge financial support by TU Wien Bibliothek through its Open Access Funding Programme.

ASJC Scopus subject areas

  • General Earth and Planetary Sciences


Dive into the research topics of 'Assessment of Material Layers in Building Walls Using GeoRadar'. Together they form a unique fingerprint.

Cite this