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dr.ing. H. Aghababaei (Hossein)

Assistant Professor

About Me

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.

 

Expertise

Earth & Environmental Sciences
# Scattering
# Synthetic Aperture Radar
# Tomography
Engineering & Materials Science
# Covariance Matrix
# Scattering
# Synthetic Aperture Radar
# Tomography
Physics & Astronomy
# Synthetic Aperture Radar

Organisations

Research


Publications

Recent
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, Article 5208214. 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), Article 555. Advance online publication. 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, Article 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), Article 1960. Advance online publication. 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. Advance online publication. https://doi.org/10.1016/j.asr.2021.07.043

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Contact Details

 
 

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

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

Organisations

University of Twente Drienerlolaan 5
7522 NB Enschede
+31 (0)53 489 9111
info@utwente.nl
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