101 citations · 133 across the 5 of their papers we have counts for
6 papers
Rapid Loss of the Sierra Nevada's Largest Trees Driven by Fire
Fabien H. Wagner, Dan J. Dixon, Christopher W. Woodall +15
Large trees disproportionately contribute to biomass storage, habitat structure, and ecosystem functioning. However, their distribution and health dynamics remain poorly quantified…
High Resolution Tree Height Mapping of the Amazon Forest using Planet NICFI Images and LiDAR-Informed U-Net Model
Fabien H Wagner, Ricardo Dalagnol, Griffin Carter +19
Tree canopy height is one of the most important indicators of forest biomass, productivity, and ecosystem structure, but it is challenging to measure accurately from the ground and…
Sentinel-1 SAR Based Weakly Supervised Learning For Tropical Forest Mapping
Adugna Mullissa, Sassan Saatchi
Tropical forests play an important role in regulating the global carbon cycle and are crucial for maintaining the tropical forest biodiversity. Therefore, there is an urgent need t…
Amazon's 2023 Drought: Sentinel-1 Reveals Extreme Rio Negro River Contraction
Fabien H Wagner, Samuel Favrichon, Ricardo Dalagnol +3
The Amazon, the world's largest rainforest, faces a severe historic drought. The Rio Negro River, one of the major Amazon River tributaries, reaches its lowest level in a century i…
Despeckling Polarimetric SAR Data Using a Multi-Stream Complex-Valued Fully Convolutional Network
Adugna G. Mullissa, Claudio Persello, Johannes Reiche
A Polarimetric Synthetic Aperture Radar (PolSAR) sensor is able to collect images in different polarization states, making it a rich source of information for target characterizati…
deSpeckNet: Generalizing Deep Learning Based SAR Image Despeckling
Adugna G. Mullissa, Diego Marcos, Devis Tuia +2
Deep learning (DL) has proven to be a suitable approach for despeckling synthetic aperture radar (SAR) images. So far, most DL models are trained to reduce speckle that follows a p…