Hybrid Machine Learning Forest Height Estimation from TanDEM-X InSAR
I Mansour, K Papathanassiou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Combining machine learning with physical models can significantly impact retrieval
algorithms designed to invert geophysical parameters from remote sensing data. Such …
algorithms designed to invert geophysical parameters from remote sensing data. Such …
CATSNet: a context-aware network for Height Estimation in a Forested Area based on Pol-TomoSAR data
Tropical forests are a key component of the global carbon cycle. With plans for upcoming
space-borne missions like BIOMASS to monitor forestry, several airborne missions …
space-borne missions like BIOMASS to monitor forestry, several airborne missions …
Deep Learning based View Interpolation towards Improved TomoSAR Focusing
SA Serafín-García, M Nannini, R Hänsch… - … and Remote Sensing …, 2024 - ieeexplore.ieee.org
Synthetic aperture radar tomography (TomoSAR) uses several coregistered images from
different perspectives to reconstruct a power spectrum pattern (PSP) perpendicular to the …
different perspectives to reconstruct a power spectrum pattern (PSP) perpendicular to the …
Analysis of A Deep Learning Solution for Tomosar Forest Reconstruction
Forest measurement is crucial for tracking climate change and quantifying the global carbon
cycle. Synthetic Aperture Radar Tomography has become an effective technique to realize …
cycle. Synthetic Aperture Radar Tomography has become an effective technique to realize …
Harnessing Deep Learning for TomoSAR stack enhancement
SA Serafin-Garcia, M Nannini… - EUSAR 2024; 15th …, 2024 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) tomography (TomoSAR) utilizes co-registered SAR images
from different tracks (known as a “TomoSAR stack”) to create a resolution in the height …
from different tracks (known as a “TomoSAR stack”) to create a resolution in the height …