A hybrid machine learning model combining TanDEM-X InSAR and Landsat optical data for forest height estimation.
#tandem-x
Content tagged with "tandem-x"
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.
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).
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...
Presents the hybrid AI-physical forest height estimation approach applied over Gabon, at the TerraSAR-X/TanDEM-X Science Team Meeting.
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...
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...
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...