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.
#forest height
Content tagged with "forest height"
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.
Synergizing AI and Physical Models for TanDEM-X InSAR Forest Height Estimation: A Hybrid Approach over the Gabon
Presents the hybrid AI-physical forest height estimation approach applied over Gabon, at the TerraSAR-X/TanDEM-X Science Team Meeting.
Combining AI Techniques with Physical Models: Forest Height Inversion from TanDEM-X InSAR Data Using a Hybrid Modeling Approach
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...
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...