6 papers
A Fast Methane Detection Pipeline on Board Satellites Based on Mag1c-SAS and LinkNet
Jonáš Herec, VÃt RůžiÄka, Rado PitoÅák +1
Methane is a potent greenhouse gas, and detecting leaks early via hyperspectral satellite imagery can help climate change mitigation efforts. Meanwhile, many existing hyperspectral…
SuNeRF-CME: Physics-Informed Neural Radiance Fields for Tomographic Reconstruction of Coronal Mass Ejections
Robert Jarolim, Martin Sanner, Chia-Man Hung +8
Coronagraphic observations enable direct monitoring of coronal mass ejections (CMEs) through scattered light from free electrons, but determining the 3D plasma distribution from 2D…
Fully Automatic Trace Gas Plume Detection
VÃt RůžiÄka, David R. Thompson, Jay E. Fahlen +13
Future imaging spectrometers will expand contemporary data volumes by orders of magnitude, requiring automated methods to upscale labor-intensive detection of trace gas point sourc…
Operational machine learning for remote spectroscopic detection of CH point sources
VÃt RůžiÄka, Gonzalo Mateo-GarcÃa, Itziar Irakulis-Loitxate +7
Mitigating anthropogenic methane sources is one of the most cost-effective levers to slow down global warming. While satellite-based imaging spectrometers, such as EMIT, PRISMA, an…
Optimizing Methane Detection On Board Satellites: Speed, Accuracy, and Low-Power Solutions for Resource-Constrained Hardware
Jonáš Herec, VÃt RůžiÄka, Rado PitoÅák
Methane is a potent greenhouse gas, and detecting its leaks early via hyperspectral satellite imagery can help mitigate climate change. Meanwhile, many existing missions operate in…
HyperspectralViTs: General Hyperspectral Models for On-board Remote Sensing
VÃt RůžiÄka, Andrew Markham
On-board processing of hyperspectral data with machine learning models would enable unprecedented amount of autonomy for a wide range of tasks, for example methane detection or min…