Menu:

MSc. Martijn NOTTEBAERE

Researcher

Martijn.Nottebaere@elec.rma.ac.be     +32-2-44-14198     Academic details

Research projects

SENSPORT

This project aims at developing a method based on a radio frequency radar to detect non destructively leaks in underground water transport networks. The involvement of RMA in the projects resides mainly in the image formation process of the volume below the ground surface based on radar measurements obtained through a ground penetrating radar method. Detection of water and other objects such as water pipes will also be tackled.

SENSAR

The SENSAR project aims at assessing if and how high resolution soil moisture can be extracted from SAR images at high resolution. One of the key components of the project is the large scale in-situ measurements and a model-based inversion from backscatter to dielectric constant. As a side-product of that inversion, soil roughness information is obtained and that can then be used as a hint to assist in the inversion of the SAR data. The RMA is in charge of the SAR image processing and of part of the inversion process.

Publications

  1. A. De Coster, J. L. Pérez Medina, M. Nottebaere, K. Alkhalifeh, X. Neyt, J. Vanderdonckt, and S. Lambot. Towards an improvement of GPR-based detection of pipes and leaks in water distribution networks. Journal of Applied Geophysics, 162:138-151, 2019.
  2. M. R. Ardekani, X. Neyt, M. Nottebaere, D. Jacques, and S. Lambot. GPR data inversion for vegetation layer. In Proceedings of the 15th International Conference on Ground Penetrating Radar, pages 170-175. IEEE, June 2014.
  3. M. Nottebaere, M. R. Ardekani, S. Lambot, and X. Neyt. SAR-image derived soil moisture enhancement using GPR data. In Proceedings of the 15th International Conference on Ground Penetrating Radar, pages 223-226, June 2014.
  4. Martijn Nottebaere, Mohammad Reza Mahmoudzadeh Ardekani, Pascal Druyts, Sébastien Lambot, and Xavier Neyt. Automatic 3D subsurface pipe-detection and permittivity reconstruction from GPR measurements. In Proceedings of the 20th URSI Benelux Forum, November 2014.
  5. Martijn Nottebaere, Mohammad Reza Mahmoudzadeh Ardekani, Sébastien Lambot, and Xavier Neyt. Soil moisture patterns characterized by GPR help enhancing SAR-image derived surface soil moisture. In Proceedings of the 20th URSI Benelux Forum, November 2014.