dr.ing. H. Aghababaei (Hossein)

Dr. Hossein Aghababaei has held the position of Assistant Professor at the Faculty of ITC, University of Twente since 2020. Prior to this appointment, he served as a Research Fellow in the Department of Engineering at the University of Naples, Parthenope, Italy, during the period spanning 2017 to 2019.

His research is primarily focused on synthetic aperture radar (SAR) data analysis, with a particular specialization in Polarimetric SAR (#PolSAR) and SAR tomography (#TomoSAR). His research interests are closely aligned with applications pertaining to the forestry sector, specifically the investigation of forest structures (#3D forest) through the utilization of SAR tomography. In recent years, he has been working on deep learning solutions for PolSAR & TomoSAR data analysis.

His scholarly contributions are underscored by his publication of several articles in international journals and conference proceedings, predominantly in the domains of Forest and Urban Polarimetric Tomography.

He also serves as an Associate Editor for IEEE GRSL (Geoscience and Remote Sensing Letters) and holds membership in the Nederlands Aardwetenschappelijk Congres (NAC). He actively contributes to the academic community by regularly participating as a program committee member for conferences and by serving as a reviewer for international journals within his field of expertise.

Earth & Environmental Sciences

# Scattering
# Synthetic Aperture Radar
# Tomography

Engineering & Materials Science

# Covariance Matrix
# Scattering
# Synthetic Aperture Radar
# Tomography

Physics & Astronomy

# Synthetic Aperture Radar

Faculty of Geo-Information Science and Earth Observation (ITC), Department of Earth Observation Science (EOS)

Hosseini, B., Amini, J. , Aghababaei, H., & Ferraioli, G. (2023). Enabling high-resolution micro-vibration detection using ground-based synthetic aperture radar: A case study for pipeline monitoring. Remote sensing, 15(16), 1-18. https://doi.org/10.3390/rs15163981

Aghababaei, H., Ferraioli, G. , Stein, A., & Vitale, S. (2023). Deep learning based polarimetric data augmentation: Dual2Full-pol extension. IEEE transactions on geoscience and remote sensing, 61. https://doi.org/10.1109/TGRS.2023.3299419

Yang, W., Vitale, S. , Aghababaei, H., Ferraioli, G., Pascazio, V., & Schirinzi, G. (2023). A deep learning solution for height estimation on a forested area based on Pol-TomoSAR data. IEEE transactions on geoscience and remote sensing, 61. https://doi.org/10.1109/TGRS.2023.3274395

Aghababaei, H. , & Stein, A. (2023). Speckle Reduction in SAR Images. In Spaceborne Synthetic Aperture Radar Remote Sensing: Techniques and Applications (pp. 13-44). CRC Press (Taylor & Francis). https://doi.org/10.1201/9781003204466-2

Poorazimy, M., Shataee, S. , Aghababaei, H., Tomppo, E., & Praks, J. (2023). First Demonstration of Space-Borne Polarization Coherence Tomography for Characterizing Hyrcanian Forest Structural Diversity. Remote sensing, 15(3), [555]. https://doi.org/10.3390/rs15030555

Hosseiny, B., Amini, J. , & Aghababaei, H. (2023). Structural displacement monitoring using ground-based synthetic aperture radar. International Journal of Applied Earth Observation and Geoinformation (JAG), 116, [103144]. https://doi.org/10.1016/j.jag.2022.103144

Ranjit, B. , Aghababaei, H. , Bijker, W. , & Stein, A. (2022). TomoSAR derived features for estimation of Forest Structure and Fuel load. In EUSAR 2022 - 14th European Conference on Synthetic Aperture Radar (pp. 121-125). (Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR; Vol. 2022-July). IEEE. https://ieeexplore.ieee.org/document/9944227

Shafai, S., Kumar, S. , Aghababaei, H., & Kulshrestha, A. (2022). Evaluating the effect of POA compensation on polinsar coherence for L-and-S band airborne SAR data. In 2021 IEEE International India Geoscience and Remote Sensing Symposium (InGARSS) (pp. 356-359). IEEE. https://doi.org/10.1109/ingarss51564.2021.9792001

Aghababaei, H., Ferraioli, G. , Stein, A., & Déniz, L. G. (2022). Polarization optimization for the detection of multiple persistent scatterers using SAR tomography. Remote sensing, 14(9), [1960]. https://doi.org/10.3390/rs14091960

Omati, M., Sahebi, M. R. , & Aghababaei, H. (2022). The comparative study of three nonparametric methods of SAR tomography for building reconstruction. Advances in space research, 69(4), 1743-1751. https://doi.org/10.1016/j.asr.2021.07.043

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+31534895178

h.aghababaei@utwente.nl

Visiting Address

University of Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds (building no. 19), room 1326
Hallenweg 8
7522NH Enschede
The Netherlands

Mailing Address

University of Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds 1326
P.O. Box 217
7500 AE Enschede
The Netherlands

Faculty of Geo-Information Science and Earth Observation (ITC), Department of Earth Observation Science (EOS)

University of Twente Drienerlolaan 5
7522 NB Enschede

+31 (0)53 489 9111
info@utwente.nl
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