3 papers
cs.CV2026
Plume Segmentation from MethaneSAT with Cross-Sensor Transfer Learning and Physics-Informed Postprocessing
Manuel Pérez-Carrasco, Maya Nasr, Zhan Zhang +16
Automated detection and masking of individual methane plumes from satellite imagery is important for operational emission attribution and quantification. We present a machine learn…
cs.CV2026
Deep Learning for Clouds and Cloud Shadow Segmentation in Methane Satellite and Airborne Imaging Spectroscopy
Manuel Perez-Carrasco, Maya Nasr, Sebastien Roche +12
Effective cloud and cloud shadow detection is a critical prerequisite for accurate retrieval of concentrations of atmospheric methane (CH4) or other trace gases in hyperspectral re…
physics.ao-ph2025
Capability demonstration of a JEDI-based system for TEMPO assimilation: system description and evaluation
Maryam Abdi-Oskouei, Jérôme Barré
The launch of the Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission in 2023 marked a new era in air quality monitoring by providing high-frequency, geostationary obse…