Characterization of Forest Structure Changes Exploiting TanDEM-X and GEDI Synergies
2024-07-01 L. M. Albrecht, N. Basargin, I. Mansour, R. Guliaev, N. Romero Puig, M. Pardini, K. Papathanassiou International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1-4

Discusses the synergetic combination of TanDEM-X interferometric measurements and GEDI lidar waveforms to map forest height and structure changes, comparing two TanDEM-X global coverages (2011-2013 and 2018-2020).

Correction of The Penetration Bias for InSAR DEM Via Synergetic AI-Physical Modeling: A Greenland Case Study
2024-07-01 I. Mansour, G. Fischer, R. Hänsch, I. Hajnsek, K. Papathanassiou IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, pp. 138-142

Rapid changes in the Greenland Ice Sheet require precise elevation monitoring to understand ice dynamics and predict sea level rise. X-band Interferometric Synthetic Aperture Radar (InSAR) has the potential for this purpose but is limited by microwave signal...

Combining AI Techniques with Physical Models: Forest Height Inversion from TanDEM-X InSAR Data Using a Hybrid Modeling Approach
2023-09-01 I. Mansour, K. Papathanassiou, R. Hänsch, I. Hajnsek BioGeoSAR Book of Abstracts

In the realm of artificial intelligence, specifically utilizing methodologies such as machine learning and deep learning, a conspicuous display of substantial potential across various parameter estimation problems has been demonstrated. However, such AI...

Combining TanDEM-X and GEDI Data For Mapping Forest Structure Parameter Dynamics
2023-07-01 I. Mansour, L. M. Albrecht, B. Hartweg, R. Guliaev, N. Romero Puig, J. Kim, M. Pardini, K. Papathanassiou International Geoscience and Remote Sensing Symposium (IGARSS)

The synergy of TanDEM-X interferometric data with GEDI lidar full waveform measurements for large-scale forest mapping has been addressed in a number of studies in the last years. In a number of studies, the GEDI lidar full waveforms have been used to...

Towards a Symbiosis of Model-Based and Machine Learning Forest Height Estimation Based on TanDEM-X InSAR
2022-07-01 I. Mansour, K. Papathanassiou, R. Haensch, I. Hajnsek EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, pp. 1-4

There is a necessity for developing and incorporating retrieval models, including Physical Models (PMs) and Machine Learning (ML) models for the inversion of geophysical parameters from multi-parameter SAR data. Over the last two decades, interferometric...