Hybrid Machine Learning Model for Forest Height Estimation From TanDEM-X and Landsat Data
A hybrid machine learning model combining TanDEM-X InSAR and Landsat optical data for forest height estimation.
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Content tagged with "machine learning"
Hybrid AI–Physical Modeling in Interferometric SAR: Bridging Data-Driven and Physics-Based Approaches for Enhanced Parameter Retrieval
Doctoral thesis on combining data-driven machine learning with physics-based scattering models to improve parameter retrieval from interferometric SAR.
Hybrid AI-physical Modeling for Penetration Bias Correction in X-band InSAR DEMs: A Greenland Case Study
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.
Hybrid Machine Learning Forest Height Estimation From TanDEM-X InSAR
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.
Machine Learning in Model-Based Forest Height Inversion
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...
Towards a Symbiosis of Model-Based and Machine Learning Forest Height Estimation Based on TanDEM-X InSAR
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...
Automated Map Generation from Optical EO Data
A pipeline to generate OpenStreetMap-style vector maps from very-high-resolution optical imagery.
Forest Height Retrieval from TanDEM-X InSAR
A hybrid AI-physical model combining data-driven learning with electromagnetic scattering models for forest height retrieval from TanDEM-X InSAR.
Foundation Models for Earth Observation
Exploring transfer learning and adaptation of large-scale vision foundation models to SAR and optical remote sensing tasks.
Penetration Bias Correction in X-band InSAR DEMs (Greenland)
A hybrid AI-physical method to correct penetration bias in X-band InSAR digital elevation models over the Greenland Ice Sheet.