<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Islam Mansour</title><description>Islam Mansour is a postdoctoral researcher at UniBw Munich working on foundation models for SAR and optical Earth observation. PhD from ETH Zurich on hybrid AI-physical modelling for forest height and biomass retrieval from TanDEM-X InSAR.</description><link>https://imansour.net/</link><item><title>[Publication] Hybrid Machine Learning Model for Forest Height Estimation From TanDEM-X and Landsat Data</title><link>https://imansour.net/publications/2026-05-14-mansour-hybrid-machine-learning-2026/</link><guid isPermaLink="true">https://imansour.net/publications/2026-05-14-mansour-hybrid-machine-learning-2026/</guid><description>A hybrid machine learning model combining TanDEM-X InSAR and Landsat optical data for forest height estimation.</description><pubDate>Thu, 14 May 2026 00:00:00 GMT</pubDate></item><item><title>[Publication] Hybrid AI–Physical Modeling in Interferometric SAR: Bridging Data-Driven and Physics-Based Approaches for Enhanced Parameter Retrieval</title><link>https://imansour.net/publications/2025-12-07-mansour-hybrid-ai-physical-2025/</link><guid isPermaLink="true">https://imansour.net/publications/2025-12-07-mansour-hybrid-ai-physical-2025/</guid><description>Doctoral thesis on combining data-driven machine learning with physics-based scattering models to improve parameter retrieval from interferometric SAR.</description><pubDate>Sun, 07 Dec 2025 00:00:00 GMT</pubDate></item><item><title>[Publication] Hybrid AI-physical Modeling for Penetration Bias Correction in X-band InSAR DEMs: A Greenland Case Study</title><link>https://imansour.net/publications/2025-06-11-mansour-hybrid-a-iphysical-modeling-2025a/</link><guid isPermaLink="true">https://imansour.net/publications/2025-06-11-mansour-hybrid-a-iphysical-modeling-2025a/</guid><description>A hybrid AI-physical method to correct penetration bias in X-band InSAR DEMs over the Greenland Ice Sheet, parameterising the vertical structure function via machine learning.</description><pubDate>Wed, 11 Jun 2025 00:00:00 GMT</pubDate></item><item><title>[Publication] Hybrid Machine Learning Forest Height Estimation From TanDEM-X InSAR</title><link>https://imansour.net/publications/2025-01-01-mansour-hybrid-machine-learning-2025a/</link><guid isPermaLink="true">https://imansour.net/publications/2025-01-01-mansour-hybrid-machine-learning-2025a/</guid><description>A hybrid model-based and machine learning approach to forest height estimation from TanDEM-X InSAR, validated over tropical biomes including Gabon and the Amazon.</description><pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate></item><item><title>[Publication] Characterization of Forest Structure Changes Exploiting TanDEM-X and GEDI Synergies</title><link>https://imansour.net/publications/2024-07-01-albrecht-characterization-2024/</link><guid isPermaLink="true">https://imansour.net/publications/2024-07-01-albrecht-characterization-2024/</guid><description>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).</description><pubDate>Mon, 01 Jul 2024 00:00:00 GMT</pubDate></item><item><title>[Publication] Correction of The Penetration Bias for InSAR DEM Via Synergetic AI-Physical Modeling: A Greenland Case Study</title><link>https://imansour.net/publications/2024-07-01-mansour-correction-2024/</link><guid isPermaLink="true">https://imansour.net/publications/2024-07-01-mansour-correction-2024/</guid><description>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...</description><pubDate>Mon, 01 Jul 2024 00:00:00 GMT</pubDate></item><item><title>[Publication] Synergizing AI and Physical Models for TanDEM-X InSAR Forest Height Estimation: A Hybrid Approach over the Gabon</title><link>https://imansour.net/publications/2023-10-01-mansour-synergizing-2023/</link><guid isPermaLink="true">https://imansour.net/publications/2023-10-01-mansour-synergizing-2023/</guid><description>Presents the hybrid AI-physical forest height estimation approach applied over Gabon, at the TerraSAR-X/TanDEM-X Science Team Meeting.</description><pubDate>Sun, 01 Oct 2023 00:00:00 GMT</pubDate></item><item><title>[Publication] Combining AI Techniques with Physical Models: Forest Height Inversion from TanDEM-X InSAR Data Using a Hybrid Modeling Approach</title><link>https://imansour.net/publications/2023-09-01-mansour-combining-2023/</link><guid isPermaLink="true">https://imansour.net/publications/2023-09-01-mansour-combining-2023/</guid><description>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...</description><pubDate>Fri, 01 Sep 2023 00:00:00 GMT</pubDate></item><item><title>[Publication] Combining TanDEM-X and GEDI Data For Mapping Forest Structure Parameter Dynamics</title><link>https://imansour.net/publications/2023-07-01-mansour-combining-2023-1/</link><guid isPermaLink="true">https://imansour.net/publications/2023-07-01-mansour-combining-2023-1/</guid><description>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...</description><pubDate>Sat, 01 Jul 2023 00:00:00 GMT</pubDate></item><item><title>[Publication] Machine Learning in Model-Based Forest Height Inversion</title><link>https://imansour.net/publications/2023-06-01-mansour-machine-2023/</link><guid isPermaLink="true">https://imansour.net/publications/2023-06-01-mansour-machine-2023/</guid><description>Model-based (PM) forest height inversion from Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR) measurements is today an established application demonstrated and validated at large scales for a wide variety of boreal and tropical forest sites...</description><pubDate>Thu, 01 Jun 2023 00:00:00 GMT</pubDate></item><item><title>[Publication] Towards a Symbiosis of Model-Based and Machine Learning Forest Height Estimation Based on TanDEM-X InSAR</title><link>https://imansour.net/publications/2022-07-01-mansour-towards-2022/</link><guid isPermaLink="true">https://imansour.net/publications/2022-07-01-mansour-towards-2022/</guid><description>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...</description><pubDate>Fri, 01 Jul 2022 00:00:00 GMT</pubDate></item><item><title>[Publication] Analysis of Multi-Frequency Polarimetric SAR Data over Permafrost Regions</title><link>https://imansour.net/publications/2021-02-01-mansour-analysis-2021/</link><guid isPermaLink="true">https://imansour.net/publications/2021-02-01-mansour-analysis-2021/</guid><description>Multi-frequency polarimetric SAR analysis of the 2018-2019 PermASAR airborne campaign over the permafrost region of Herschel Island, northwest Canada.</description><pubDate>Mon, 01 Feb 2021 00:00:00 GMT</pubDate></item><item><title>[Publication] 3D Matching of TerraSAR-X Derived Ground Control Points to Mobile Mapping Data</title><link>https://imansour.net/publications/2019-08-01-loesch-3d-nodate/</link><guid isPermaLink="true">https://imansour.net/publications/2019-08-01-loesch-3d-nodate/</guid><description>Machine learning algorithms for 3D matching of TerraSAR-X-derived ground control points with mobile LiDAR mapping data, for georeferencing of pole-like structures.</description><pubDate>Thu, 01 Aug 2019 00:00:00 GMT</pubDate></item></channel></rss>